Alexander Gurov, Business Development Officer

The medical industry is attracting more and more and money as people have a growing need for better and more convenient services. We will look at the healthcare industry, what prospects it has, as well as explore the types of medical apps and how much it costs to develop them.

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We look how to make a social networking site in detail, tell you about its components, advantages and disadvantages of developing it, choosing the right type of website and technology stack.

How to build a social network website from scratch and gather more than 1 billion users like TikTok

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    <ContentWrapper title="How implementing AI in media can help your company reduce freelance cost">
    Artificial intelligence (AI) is rapidly developing and is being used by more creative people: artists, designers, musicians, authors of texts in various genres, and recently neural networks were started to be used in video production: movies, TV series and commercials, and also in news websites, personal blogs and services with text and video content. According to <a class="link-dark" target="_blank" href="https://www.forbes.com/sites/joshwilson/2022/12/06/artificial-intelligence-machine-learning-and-the-future-of-entertainment/?sh=26d0aa2d6de4" rel="nofollow">Forbes</a>, the market of AI-based products for media has reached a total value of 13 billion dollars, and by 2030 it will be worth about 100 billion dollars.<br/>
    The introduction of AI in media and entertainment (M&E) will help to significantly reduce the cost of content production and reduce the risks of high-budget projects not paying off, as AI can help to estimate everything. On the other hand, artificial intelligence is also developing for ordinary users, and they use these tools to find the information they need. People stop using standard search tools and websites, which immediately leads to a drop in traffic and, consequently, advertising traffic, which is an important part of a company's revenue. This is why businesses need to seriously consider how to regain their audience and what their profits will be in the future.<br/>
    In this article, we look at several popular AI trends in the M&E industry, explore the problems that can arise when implementing AI tools and how to solve them, and cover the issue of the effective use of neural networks in the entertainment industry.

    <Title className="contentTitle" type="h2" id="trends-of-ai-in-media">Trends of AI in media</Title>
    We <a class="link-dark" target="_blank" href="https://dotwrk.com/blog/ai-in-healthcare" rel="nofollow">listed and talked</a> about three popular AI trends in healthcare. In the M&E industry everything turned upside down in November 2022, when ChatGPT, probably the most popular generative AI-product, was released, and it can write the necessary text at the user's request on any topic and in any style, even the code. The work of generative AI is still far from perfect, but it became a truly breakthrough technology for a wide variety of spheres of life and industries. We did <a class="link-dark" target="_blank" href="https://dotwrk.com/blog/can-chat-gpt-write-code" rel="nofollow">an experiment</a> where we tried to write a small plugin for Google Chrome using ChatGPT.<br/>
    Artificial intelligence already created a lot of trouble, because it affected the way people search for information online. People have become less likely to use search services and more likely to rely on AI, resulting in users not needing to visit websites that have the information they need. This results in lower ad display and, as a consequence, lower ad revenue. This is a problem for advertisers and website owners, however, at the same time AI technologies found application in several areas of media, which we will discuss next.

    <Img class={['col-12']} width="1981px" height="800px" src="/images/blog/ai-in-media-pic-1.png" alt="Trends of AI in media"/>

    <Title className="contentSubtitle" type="h3" id="personalization">Personalization</Title>
    One of the main reasons why AI emerged in the M&E industry is the personalization of services for each user. This aspect touches several areas that improve the accuracy of unique and customized offers:<br/>
    * Analysis of user behavior and sentiment;
    * Building multiple scenarios to provide a personalized user experience;
    * Developing and training neural networks for real-time user experience.<br/>

    Netflix is one of the biggest media companies who incorporate neural networks into their analytics tools and recommendation system. They also implemented artificial intelligence in their video encoding algorithms, which allows them to compress the picture without loss of quality, allowing users to consume less traffic and watch movies and TV series without lags and long waits for downloading.<br/>
    Also, AI tools are used for news writing, when a neural network processes large amounts of statistical data and creates a news text based on it, even without human input. This was called automated journalism, and these technologies are already being used by major media outlets like Bloomberg and The Washington Post. And recently, Google announced the creation of its <a class="link-dark" target="_blank" href="https://techcrunch.com/2023/07/20/google-reportedly-testing-ai-tool-write-news-articles/" rel="nofollow">own AI tools</a> for creating news content.<br/>
    In general, natural language processing, audio and video generation and content creation technologies based on big data and deep learning algorithms will be the key for many companies in different aspects.<br/>
    * Content creation will be faster, easier and cheaper, as AI tools will become more available.
    * AI-powered tools will help companies with better understanding of their users, so they will be able to create more precise recommendations and personalized advertising offerings that solve the widespread «paradox of choice» that users regularly face when trying to find a movie or TV series to watch.<br/>

    These things no longer seem like something fantastic.

    <Title className="contentSubtitle" type="h3" id="creating-content">Creating content</Title>
    When ChatGPT emerged, many authors adapted it as a tool to help create content: generate texts, create colorful illustrations, short videos and audios that will best fit the users' requirements and the context of the media. It's pretty hard to argue that generative AI revolutionized content marketing.<br/>
	Also neural networks improved the designers and branding authors workflow. The tools became faster, easier, more accessible and more effective, and they make it possible to create well-crafted and unique advertising solutions for each target audience with its own requirements and preferences.<br/>
	But it's important to keep in mind that using pure and raw AI output can lead to legal problems, which we'll discuss below. So people in creative occupations will still be in demand, but AI will make it possible to optimize and speed up their work, as well as reduce the costs of hiring part-time employees and freelancers.

    <Title className="contentSubtitle" type="h3" id="improved-advertising-and-increased-revenue">Improved advertising and increased revenue</Title>
    Nowadays, most advertising approaches are outdated and don't make enough profit for companies, so artificial intelligence comes to the rescue here. As we wrote above, AI solutions increase the personalization of customer’s offers, which means they will be able to analyze user behavior in more detail and offer ads to those who will actually be interested and take advantage of the offer. This can also increase revenue from sales of a company's services.

    <Title className="contentTitle" type="h2" id="challnges-and-threats-of-ai-in-media">Challenges and threats of AI in media</Title>
    The introduction of artificial intelligence brings a lot of new opportunities for companies and users, but at the same time it brings several problems and even threats for everyone, especially when used carelessly. Let's take a look at what problems can arise with AI implementation in the M&E industry.

    <Img class={['col-12']} width="1981px" height="800px" src="/images/blog/ai-in-media-pic-2.png" alt="Challenges and threats of AI in media"/>


    <Title className="contentSubtitle" type="h3" id="high-cost-of-implementation">High cost of implementation</Title>
    This is perhaps one of the biggest challenges facing companies that want to implement AI solutions into their business. You will most likely have to train neural networks on large amounts of data and customize them to your needs, which can be costly, and as a result, the cost of implementing AI tools can add up to the following factors:

    <Img class={['col-12']} width="1981px" height="1000px" src="/images/blog/ai-in-media-pic-3.png" alt="AI tools implementing cost factors"/>

    When implementing AI into their systems, it is important for media companies to understand whether it is worth the effort and money spent in the long run. However, such a problem is slowly fading away, because more and more AI tools become generally available and their usage will become a regular thing.

    <Title className="contentSubtitle" type="h3" id="loss-of-traffic-and-reduced-ad-revenue">Loss of traffic and reduced ad revenue</Title>
    Yes, you got it right: some AI tools help to increase traffic and ad revenue, and some tools decrease them. This thing became an issue since generative AI appeared in everyone’s lives, particularly ChatGPT, which generates information based on a user's query. Thanks to AI tools, users don't have to go to web pages to search for companies. That’s why a significant part of the traffic from the site may disappear, and thus the revenue from display ads will decrease.

    <Title className="contentSubtitle" type="h3" id="job-extinction">Job extinction</Title>
    AI solutions are efficient solutions for creating content or analyzing data, and they can handle their tasks faster than humans. This is good news for companies that want to get results quickly and cheaply, but on the other hand it is bad news for some professionals: journalists, copywriters, designers, musicians and many other multimedia content creators.<br/>
	People of artistic occupations already thought about their substitution by neural networks and started to adapt to new conditions. We want to reassure you that the trend to total disappearance of some jobs is not expected, but the work of many professionals will change, and you need to adapt to global changes to remain in demand. Moreover, it is too early to talk about full-fledged substitution by AI tools because of the next problem of artificial intelligence.

    <Title className="contentSubtitle" type="h3" id="quality-of-generated-content">Quality of generated content</Title>
    AI-based tools and algorithms are actively developing and improving nowadays, however so far they make a lot of mistakes and errors that need to be corrected manually or generate a lot of low-quality and fake content. Therefore, companies have to implement verification tools as well to validate the results.

    <Title className="contentSubtitle" type="h3" id="ethical-and-legal-issues">Ethical and legal issues</Title>
    Besides the quality aspects, there are also legal and ethical issues, such as copyright. <a class="link-dark" target="_blank" href="https://www.copyright.gov/rulings-filings/review-board/docs/a-recent-entrance-to-paradise.pdf" rel="nofollow">American</a> and <a class="link-dark" target="_blank" href="https://intellectual-property-helpdesk.ec.europa.eu/news-events/news/intellectual-property-chatgpt-2023-02-20_en" rel="nofollow">European</a> legislation does not protect information generated by artificial intelligence by copyright, which can lead to serious problems in the work of mass media, in particular, with their financing.<br/>
    Moreover, neural networks are trained on content from the Internet, some of which is also protected by copyright. It is alarming to authors that technology is being trained on their material and content, but in return they receive no compensation or mention of their authorship.

    <Title className="contentSubtitle" type="h3" id="fake-news-and-junk-content">Fake news and junk content</Title>
    Most people are familiar with the concept of fake news, which has become a big problem in our society as it is increasingly difficult to distinguish them from real news. Artificial intelligence has made it simple to create fake content, and the authors who create the queries don't even have to try. Neural networks don't know where is true and where is false (this is one aspect of neural network training), so without good user verification of the result, there is a high chance of misinformation, which can lead to loss of audience loyalty, traffic, revenue and reputation.

    <Title className="contentTitle" type="h2" id="how-to-effectively-use-ai-in-communication-and-media">How to effectively use AI in communication and media</Title>
    Besides the most obvious way to use neural networks, namely generating multimedia content, cost optimization and personalization of products and services, there are several other ways to utilize AI in the communication and media industry.

    <Title className="contentSubtitle" type="h3" id="improving-workflows-with-video-content">Improving workflows with video content</Title>
    <a class="link-dark" target="_blank" href="https://www.techsmith.com/blog/video-statistics/" rel="nofollow">Most of the people receive information through video</a>, which means that this type of content needs to be handled in many aspects. Recently, labeling, adding subtitles and other important metadata became an important part of working with video. Modern tools based on neural networks are now doing a great job with this task.<br/>
	Also in this article we mentioned Netflix's use of AI algorithms for encoding and compressing video without much loss of quality. This way users can quickly download content in good quality even with slow internet speeds.

    <Title className="contentSubtitle" type="h3" id="supporting-users-with-ai-chatbots">Supporting users with AI chatbots</Title>
    Our world is changing rapidly, information is becoming very plentiful, so society is developing a clip mentality, which makes many people expect their needs to be met instantly and their problems to be solved quickly. Human support services may not be able to cope with such a task, so smart chatbots come to the rescue, which will be able to answer questions and solve users' problems at any time of the day. Advancements in technology are allowing chatbots to become more advanced and offer users comprehensive support that is indistinguishable from human support. The introduction of modern AI in user support creates a human image of the company and increases customer loyalty through high quality customer interaction. Where customer loyalty is, there are high engagement rates and good monetization.

    <Title className="contentSubtitle" type="h3" id="fighting-fake-news">Fighting fake news</Title>
    The reasons for the rapid development of fake news are unscrupulous journalists and... neural networks, which generate news based on already created texts without the ability to distinguish truth from lies. This is how they are trained.<br/>
	However, the creators of AI tools figured out how to fight fake news with the help of modern technology, in particular, such <a class="link-dark" target="_blank" href="https://www.bbc.com/news/technology-39707642" rel="nofollow">algorithms developed in Google</a>, which scan websites and check whether the information is trustworthy for users. Of course, the algorithm is not accurate, but it is a serious step in the fight against fake news.

    <Title className="contentSubtitle" type="h3" id="content-moderation">Content moderation</Title>
    This is a similar area to the previous one where AI can be used effectively. A company can check its resources, including advertising, for harmful content, such as those related to hate speech, bullying or violence. This way, users will feel safe and have a positive experience with your products.

    <Title className="contentTitle" type="h2" id="ai-in-media-conclusion">Conclusion</Title>
    Artificial intelligence has a huge potential for use in various spheres: from mining to healthcare. And in the media and entertainment industry, AI solutions can be used to their full potential to make creative ideas come to life, verify the authenticity of information, automate work processes related to various content, and so on. However, it is important to remember that AI solutions cannot yet fully replace humans; they can only serve as auxiliary tools. Therefore, it is important to check everything that neural networks do and make corrections if necessary, and then the results of such «joint» efforts will bring excellent results.<br/>
    In this article, we looked in detail at AI in media and entertainment, what neural networks can bring to users and businesses, and what problems they can create for them. We tried to focus on issues related to advertising and revenue generation, but as it turns out, there are many other important aspects to keep in mind.<br/>
    Our team works on several M&E and news industry related projects where we successfully implemented AI solutions. In one of the them we are developing AI-based applications in multiple domains, including:<br/>
    * Generation of short commerce texts in the required tone-of-voice, e.g. captions for the product images.
    * Generation of the content based on the pre-collected and systematized information, including articles and texts previously written by the editorial team.
    * Generation of the content based on statistical, historical and unchangeable information, e.g. writing the reviews to the products, venues, cars, etc.<br/>

    Each of these directions gave us promising results and one of the biggest achievements was the cost reduction on the freelance work because neural networks could cover these project needs.<br/>
    If you have a project where you would like to implement AI in media products, but don't know how to do it effectively, <a class="link-dark" href="#contact">fill out the form</a> on our website and we will be happy to answer all your questions.

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We look at some several AI trends in media industry and explore some problems that can arise when implementing AI tools.

How implementing AI in media can help your company reduce freelance cost

We compare headless and traditional CMS, their advantages and disadvantages and where to use them best.

Headless CMS vs. Traditional CMS: why the «headlessness» success is changing monolithic solutions

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    <ContentWrapper title="How to implement healthcare data security tools to exclude breaches of more than 40 million patient records">
    Technology is becoming more advanced, and digitalization is beginning to affect many social aspects of our lives, including medicine, where a big bunch of tools is becoming available every year. New technologies allow for better checkups, more accurate diagnoses, and more effective treatments. We wrote about some medical technologies based on artificial intelligence in detail <a class="link-dark" target="_blank" href="https://dotwrk.com/blog/ai-in-healthcare" rel="nofollow">in this article</a>. New technologies in medicine make it possible to create, store and utilize disease information digitally and store it in electronic health records (EHR). This is a faster, more convenient, and more understandable way for doctors and healthcare providers to access standardized patient information.<br/>
    However, electronic health records also come with many dangerous problems, since medical information is classified as sensitive, which means it is a very valuable product for attackers. According to <a class="link-dark" target="_blank" href="https://www.experian.com/blogs/ask-experian/heres-how-much-your-personal-information-is-selling-for-on-the-dark-web/" rel="nofollow">Experian</a>, a single electronic patient card can be worth up to $1,000 on the darknet, as it stores a large amount of personal data like date and place of birth, residential address, bank card details and more, and <a class="link-dark" target="_blank" href="https://www.healthcare.digital/single-post/2018/07/17/cost-of-healthcare-data-breach-is-408-per-stolen-record-x3-industry-average-says-ibm-and" rel="nofollow">HealthTech</a> estimates that the value of medical data is 3 times higher than the value of non-medical data. And while all medical information used to be recorded in a paper medical record and stored only inside the hospital in a file cabinet, nowadays an electronic medical database can be easily hacked and stolen if hospital computers have poor security features.<br/>
    Healthcare providers are relying now more than ever on trusted technology to handle patient data that won't allow it to be compromised. In this article, we'll take a closer look at the legal and technological regulations for protecting information, what problems arise with healthcare data security, and what you need to do to reduce the risks of patient data being compromised. **Spoiler:** it is not only about the development of hospital IT infrastructure, but also about the skills and knowledge of medical staff about information security.

    <Title className="contentTitle" type="h2" id="about-data-security-in-healthcare">About data security in healthcare</Title>
    There is much to be said about information security and data security in particular, but in short, data security is about creating measures that aim to protect sensitive data from unauthorized access and interference. The more secure the data, the better, but it is also important that the developed tools should also be user-friendly.

    <Title className="contentSubtitle" type="h3" id="healthcare-data-security-standards-and-legal-aspects">Healthcare data security standards and legal aspects</Title>
    Data security in healthcare is highly regulated in the US and Europe, and these laws strictly define what data must be protected and in what ways it must be protected.<br/>
    In the US, data security is governed by several laws, and the most basic is the Health Insurance Portability and Accountability Act of 1996 (<a class="link-dark" target="_blank" href="https://www.hhs.gov/hipaa/index.html" rel="nofollow">HIPAA</a>), which includes privacy rules and security regulations. This act sets national healthcare data security standards for protecting patients' personal information and their medical records, which may be strengthened or further regulated by each state's internal regulations. According to <a class="link-dark" target="_blank" href="https://www.beckershospitalreview.com/healthcare-information-technology/50-things-to-know-about-healthcare-data-security-privacy.html" rel="nofollow">Becker's Hospital research</a>, confidential information is defined as:<br/>
    * Patient's name;
    * Date of birth, death, admission and discharge from hospital;
    * Contact information: phone numbers and e-mail;
    * Residential address;
    * Insurance information;
    * Electronic medical records, including graphic records;
    * Biometric data: fingerprints, retinal scans, voice recordings;
    * Other identification documents: passport, driver's license and so on.<br/>

    Security rules require healthcare data security companies to organize proper data protection at the physical and software level, and there are requirements and guidelines for security management and troubleshooting.<br/>
    In Europe the requirements for data security in healthcare are more strict than in the US, perhaps even the toughest in the world. Medical data protection in the European Union has been regulated by the <a class="link-dark" target="_blank" href="https://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=CELEX:31995L0046:EN:HTML" rel="nofollow">European Union’s Data Protection Directive 95/46/EC of 24 October 1995</a>, which states that medical data may only be collected and processed lawfully, only under strict security requirements, and only for specified purposes. Organizations are responsible for the data collected, and they must also comply with several important principles that relate to the following aspects:<br/>
    * Protection of fundamental human rights, including the protection of personal data.
    * Data collection and processing must be transparent.
    * It is essential to be notified in the event of data leaks.
    * The ability of access, editing, deletion and blocking of data.
    * Penalty, including criminal penalties, for serious violations.<br/>

    It is important to understand how US healthcare data security regulations differ from European ones. These regulations differ in their approach to information protection. In Europe, legislation is developed in a coordinated manner by all European countries in the form of common standards **for all industries at once**, which are then transformed into laws for each individual country. In the US, regulations work differently because there are no uniform data protection laws, but rather regulations are developed **for each individual industry**. Some states have multiple privacy laws, but it is still not centralized as in Europe. <br/>
    Despite differences in the principles of personal data protection regulations, all countries are making efforts to build a robust infrastructure, and there are several important reasons for this, which we discuss below.

    <Title className="contentSubtitle" type="h3" id="the-importance-of-data-security-in-healthcare">The importance of data security in healthcare</Title>
    It is obvious that any organization that stores valuable information is vulnerable to malicious attacks, but the risks are unusually high for healthcare organizations, and there are several reasons for the importance of data security in healthcare:<br/>
    * Patient data contains a lot of valuable sensitive information: personal information, payment and insurance information, and more. Therefore, as we wrote above, its value on the darkweb can be several times higher than any other information.
    * Medicine is developing very rapidly, especially digital technologies in this industry. However, medical data stores are nothing special in terms of healthcare data security, and yet they store a lot of valuable information that attracts a large number of attackers.
    * Medical personnel work with patient data mostly remotely, which means they may receive it via unprotected wireless network protocols.
    * Moreover, medical personnel are highly overworked as they handle a large number of patients and as a result, data security is not a priority for doctors and nurses.<br/>

    Multiple technical and human reasons make the healthcare industry can cause a lot of healthcare data security challenges which we describe in the next section.

    <Title className="contentTitle" type="h2" id="healthcare-data-security-challenges">Healthcare data security challenges</Title>
    When the question of protecting medical data comes up, the first thing to deal with is the reasons why vulnerabilities may occur in the system. Healthcare organizations are at great risk because their data is very valuable to attackers. We will list some of the healthcare data security challenges that can create problems when dealing with patient data.

    <Img class={['col-12']} width="1981px" height="1000px" src="/images/blog/healthcare-data-security-pic-1.png" alt="Healthcare data security challenges"/>

    <Title className="contentSubtitle" type="h3" id="using-an-outdated-system-and-infrastructure">Using an outdated system and infrastructure</Title>
    Many medical systems run on old hardware and outdated software that may no longer be supported by the developer, causing data security issues in healthcare. In order to minimize risks, you should only use modern hardware and fresh and regularly updated software.    
    
    <Title className="contentSubtitle" type="h3" id="malware-attack-via-email">Malware attack via email</Title>
    Sending viruses and malware through emails is one of the most popular ways to attack devices. It is getting more advanced every year and the emails are indistinguishable from real emails, i.e. from a real and verified sender. Such malicious emails can contain malicious scripts and programs that give access to sensitive information to attackers.

    <Title className="contentSubtitle" type="h3" id="data-leakage-by-dishonest-employees">Data leakage by dishonest employees</Title>
    Healthcare organizations employ a huge number of people, and some employees and vendors may steal and sell certain medical data for personal reasons. Therefore, the more employees have access to sensitive data, the more chances of data breach.

    <Title className="contentSubtitle" type="h3" id="unsecure-network-infrastructure-and-weak-passwords">Unsecure network infrastructure and weak passwords</Title>
    Most healthcare organizations work with wireless devices, which means they use wireless network protocols. On the one hand this is a convenient way to get patient data from any part of the hospital, but on the other hand such network connections may not be safe for data security. Moreover, weak passwords used by employees can be a threat to the security of personal data. Therefore, all network connections should be well secured and all employee accounts should have a strong password that is difficult to pick.

    <Title className="contentSubtitle" type="h3" id="staff-who-are-not-trained-in-digital-security-rules">Staff who are not trained in digital security rules</Title>
    Medical data can be stolen not only through malware, but also due to the carelessness of inexperienced and untrained employees. They may breach security protocols or fail to complete work on their devices, which can be taken advantage of by attackers to steal medical data. Therefore, it is important that employees know how to properly use technology and equipment to follow security protocols, and it is also important to regularly review employees' knowledge of information security.

    <Title className="contentTitle" type="h2" id="ways-to-protect-medical-data">Ways to protect medical data</Title>
    There are many tools, guidelines, and security protocols for protecting health data, and the mix will depend on what kind of data you collect and how you store it. For example, some data, such as patient insurance information or records of medical exams, is not needed by all employees of a healthcare facility. Of course, the following methods do not provide a 100% guarantee of full protection of medical data, and healthcare organizations need to choose a combination of tools depending on their activities and needs, but they significantly improve the security of data storage and use. Among the most popular methods of information protection are the following:

    <Img class={['col-12']} width="1981px" height="800px" src="/images/blog/healthcare-data-security-pic-2.png" alt="Ways to protect medical data"/>

    <Title className="contentSubtitle" type="h3" id="encrypting-medical-data">Encrypting medical data</Title>
    Any sensitive information, regardless of the industry in which it is used, must be encoded with strong protocols and have strong encryption keys. Data encryption arguably imposes the highest level of security and should therefore be used to protect sensitive information.

    <Title className="contentSubtitle" type="h3" id="using-antivirus-technology-solutions">Using antivirus technology solutions</Title>
    Patient data stores must be securely protected against viruses, ransomware, and other threats from malware. This is achieved by utilizing comprehensive antivirus solutions and updating them regularly. This way the system remains safe even for the most advanced viruses and threats.

    <Title className="contentSubtitle" type="h3" id="system-monitoring">System monitoring</Title>
    When using systems with important data that can be stolen, it is important to monitor all the activities that have taken place in it. There are several solutions that can record who has accessed, added, modified, moved and deleted data, and if suspicious activities are detected, such as unauthorized individuals obtaining information or employees who should not be in possession of such information, management will be alerted.

    <Title className="contentSubtitle" type="h3" id="multi-factor-authentication-and-additional-verification">Multi-factor authentication and additional verification</Title>
    Using complex passwords is an important part of securing medical data systems, but they are difficult for ordinary employees to use. This is where additional steps in identity authentication come into play, for example, receiving a verification code via email or SMS to an employee's device directly seriously increases the resilience of the system and as a result prevents valuable information from being compromised.<br/>
    The zero-trust principle is also a good thing to implement. It states that all data, connections and other interactions that occur internally and externally within an organization must be validated, after which new information is fed into the system and new accounts are granted access.

    <Title className="contentSubtitle" type="h3" id="training-employees-on-the-information-security-basics">Training employees on the information security basics</Title>
    Employee negligence can destroy all the layers of protection for medical systems, so employees need to know how to properly use the systems to protect data and prevent data breaches.

    <Title className="contentTitle" type="h2" id="our-experience-in-developing-healthcare-data-security-solurions">Our experience in developing healthcare data security solutions</Title>
    Our team has a lot of experience in creating medical applications. For example, we worked on a <a class="link-dark" target="_blank" href="https://dotwrk.com/cases/healthcare-app" rel="nofollow">healthcare application</a> that allowed users to enter information about their own well-being and, as a result, generate reports that allow doctors to see symptoms of illness and make decisions about prescribing treatment.<br/>
    We redesigned the application infrastructure in the form of microservices built on a new framework, Symfony, which is considered one of the most secure solutions currently available. Implementing the product in the form of microservices is also considered to be an efficient solution that allows you to work on different parts of the product independently, while keeping the application available to users.<br/>
    We have also adapted all processes in the product to the US and Canadian legal requirements of HIPAA and PIPEDA respectively. This is an important step for all applications that have to provide data security healthcare. After all these changes the application also became faster, code quality increased significantly, and marketing campaigns attracted 15,000 new users over the past year.

    <Title className="contentTitle" type="h2" id="web-developers-cost-conclusion">Conclusion</Title>
    Developers of healthcare data security companies follow a vast array of requirements that ensure the safe and uninterrupted operation of hospitals and clinics. This is outlined in both basic data security requirements and regulatory laws, which policy makers continue to develop and adapt to the current level of technology. However, it's not only developers who need to keep an eye on security, but also healthcare organization leaders: it's important to provide regular training to employees, and oversight to ensure that sensitive and confidential information is not stolen by attackers.<br/>
    We hope that this article helps you understand the current regulations for healthcare data security and what tools can be used to increase the system's resilience to hacker threats. If you have an idea to create a healthcare product, but you have problems with its implementation and you ask a lot of questions, then <a class="link-dark" href="#contact">fill out the form</a> on our website, and we will quickly contact you and answer all your questions and give some hints on creating a data security healthcare app.

    <AuthorInfo image="/images/authors/1.jpg"
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We take a closer look at the legal and technological regulations for protecting information

How to implement healthcare data security tools to exclude breaches of more than 40 million patient records

We go through some factors that affect web application development cost.

10 major factors that affects the web development cost in 2024

In this article we talk about how to create e-learning website, review technologies and tools that can be used for development and cover the approximate development cost and timing issues.

How to create e-learning website in 2024 and have hundreds millions of users like Coursera

<Wrapper emptyHeading backgroundColor="gray">
    <ContentWrapper title="What Distinguishes a SaaS Platform from Regular Software Applications">
	When people think about software, they usually have in mind standalone programs that are installed on user’s devices. This was the reality for decades until «software-as-a-service» (SaaS) solutions came to market due to the rise of cloud technologies. SaaS technologies are evolving every year. More than <a class="link-dark" target="_blank" href="https://pages.bettercloud.com/rs/719-KZY-706/images/2020_StateofSaaSOpsReport.pdf" rel="nofollow">70% of software applications</a> are SaaS-based, and the market for SaaS technologies is already estimated at <a class="link-dark" target="_blank" href="https://www.gartner.com/en/newsroom/press-releases/2022-10-31-gartner-forecasts-worldwide-public-cloud-end-user-spending-to-reach-nearly-600-billion-in-2023" rel="nofollow">$195 billion</a>.<br/>
	Using SaaS products has many advantages for end users, but it also has its own nuances. In this article, we analyze what «software as a service» is, what distinguishes SaaS from regular software applications, their advantages and disadvantages, and when it is better to choose between developing SaaS products or traditional software.<br/>

    <Title className="contentTitle" type="h2" id="software-before-saas">Software before SaaS</Title>
	People were buying desktop software from vendors and installing it locally on their devices for decades. They managed their own settings of their hardware, data storage, network, security and other infrastructure, so users were responsible for correctly configured and working software. Also customers used to buy the software for a long time, for example, for several years, and if a customer is a big company, then they used to buy the software for each of its employees separately.<br/>
	This way of software distribution was no longer suitable for users, especially for SMB owners who were not comfortable hiring IT-specialists to install and configure programs for a few people. Therefore, the «software-as-a-service» distribution model appeared as an alternative to standalone software.<br/>

    <Title className="contentTitle" type="h2" id="saas-definition">What is SaaS?</Title>
	If we look at this type of software from the point of view of users, a «software-as-a-service» application is software that offers a ready-to-use solution through browser-based or mobile applications without the need to install it on the device. These applications do not require the purchase of expensive hardware and complex customization, which is good for a wide range of users.<br/>
	For vendors a SaaS application is hosted in cloud storage and made available to the user via the web or APIs. SaaS is distributed on a subscription or pay-as-you-go (PAYG) basis model, which allows for flexible pricing of services.<br/>

    <Title className="contentSubtitle" type="h3" id="types-of-saas-applications">Types of SaaS applications</Title>
	A lot of software products you use are SaaS products that can be customized for your company size, number of employees, customers and many more. Here are a few of the main types of SaaS products:<br/>
    <Img class={['col-12']} width="1981px" height="608px" src="/images/blog/saas_pic_1.png" alt="Types of SaaS applications"/>
    * **Customer Relationship Management (CRM)** systems that allow you to control customer communication channels and automate sales, like Salesforce, Hubspot, Microsoft Dynamics, and SugarCRM services.
    * **Enterprise Resource Planning (ERP)** systems allow you to automate all processes and activities: HR, accounting, marketing and sales. Examples of ERP SaaS include Sage X3, Odoo ERP, Epicor Kinetic and others.
    * **Project management and team collaboration tools** like Jira, Trello, ClickUp, Monday and Slack.
    * **Other examples of SaaS products** include all Google services, Microsoft 365, Figma, Canva and other text, data and multimedia tools.<br/>

    <Title className="contentTitle" type="h2" id="saas-difference">Difference between SaaS and regular software applications</Title>
	There are few significant differences between a SaaS product and regular software applications. Let's take a look at what distinguishes a SaaS platform from regular software applications.<br/>

    <Title className="contentSubtitle" type="h3" id="saas-development-tools">Development tools</Title>
	There is a big technological difference between the programming languages and development tools for SaaS solutions and traditional apps that are installed on a device, and the main difference between the two is the technology stack.<br/>
	SaaS application is a web application for the most part that is accessible through a browser or client application on the device and it will be developed using a web stack (HTML, CSS, JS and backend frameworks) and if needed to perform special computations you can also use scripts for computing and data processing on the server side that are written with high performance languages such as C/C++.<br/>
	Regular applications are desktop and mobile applications that require native tools and a completely different stack compared to web applications - Kotlin and Swift for Android and iOS respectively, C# and the .NET virtual machine for Windows, and you can also use React Native and Electron frameworks if you need the capabilities of web languages.<br/>

    <Title className="contentSubtitle" type="h3" id="saas-installation">Installation and customization</Title>
	A SaaS product does not require installation. Users will only need a few minutes to log into a browser or install a client application that acts as a browser, create an account and start using your SaaS application.<br/>
	At the same time, installing stationary software can take a lot of time and effort, because specialists need to set up the entire infrastructure for the program to work: server hardware with file systems, databases, network protocols, security and many more. You will also have to spend even more time if you need to integrate standalone software with other services and systems.<br/>
	The situation with customization is as follows. Many SaaS products are not flexibly customizable and their capabilities are managed by the subscription cost. Regular applications are highly customizable and can be adapted to any user's needs. This is important to keep in mind when deciding which products you will offer: simple or feature-rich with a bunch of customizations.<br/>

    <Title className="contentSubtitle" type="h3" id="saas-licensing">Licensing</Title>
	Traditional software is distributed on a one-time fee or multi-year contracts. This is due to the complexity of installation and setting up, the duration of use, and the need to prepare stable versions of products that will be used without the need for constant updates.<br/>
	At the same time, SaaS products are distributed on a more regular subscription basis: monthly or annual. Moreover, vendors have the option to update services regularly, while users have the option to pay only for what they use.<br/>

    <Title className="contentSubtitle" type="h3" id="saas-cost">Cost</Title>
	SaaS platforms cost less than regular software because they are distributed on a monthly subscription model, and also because of risks of users leaving service providers with high prices comparable to regular software cost. Moreover, these platforms often offer competitive rates for companies with a large number of employees.<br/>
	Traditional desktop software must be purchased on a per-user basis, which can be an expensive option, especially if organizations have many employees.<br/>

    <Title className="contentSubtitle" type="h3" id="saas-security">Security and privacy</Title>
	This is one of the main reasons why traditional software still exists. This is where it greatly beats SaaS solutions in the «SaaS platform vs regular software applications» competition. If customers use standalone software, they have complete control over their data as it is located in a private storage.<br/>
	A SaaS involves placing the user's files in the provider's cloud storage, which compromises the privacy of the data. This makes the service vulnerable to hackers as they can get the data of many customers.<br/>
	More and more private cloud storage is appearing at the moment and this is a good sign for companies who are worried about privacy, such as banks. So it's only a matter of time before they move to SaaS solutions.<br/>

    <Title className="contentTitle" type="h2" id="saas-benefits-and-drawbacks">Benefits and drawbacks of SaaS</Title>
	SaaS can be very valuable to your business for many reasons. Let’s look at some benefits of SaaS products:<br/>
    * **User Convenience.** They are free from the problems of finding the suitable hardware, long installation and configuration, so they just use SaaS products anywhere from any device that has internet access instead.  Users also automatically receive all necessary updates and bug fixes for all necessary kinds of devices.
    * **Low cost.** Users don't have to pay huge sums of money for expensive services. Instead, they pay a small cost on a regular basis. Moreover, users can pay only for the functionality they use and can also cancel the paid subscription if they no longer need the service.
    * **Scalability.** SaaS are hosted in scalable cloud storage, so there is no need to purchase an additional server. Users can scale the product in seconds by updating their subscription plan.
    * **Reliability.** The cloud is a network of servers spread all over the world, which means that if there is a failure in one place, it will not affect the SaaS product performance.<br/>

    Also SaaS products have a number of drawbacks that are important to some users:<br/>
    * **Privacy.** This is one of the main issues that prevents companies from choosing SaaS as working tools. As we wrote above, user data is stored on the service provider's cloud storage, which can be insecure for privacy and it can be a vulnerability to hackers.
    * **No flexible customization.** Some SaaS cannot be customized as this is controlled by the service provider. You have the option to customize standalone software to suit your requirements, which may require hiring an IT professional for installation and customization.
    * **Total dependence on internet connection.** A browser-based application may have lower performance compared to a standalone application because all the calculations are done remotely and this data needs to be transmitted over the internet. And if there is no connection, there will be no way to work with the SaaS solution. Therefore, users need a stable and fast internet connection to get rid of this factor.<br/>

    <Title className="contentTitle" type="h2" id="saas-conclusion">Conclusion</Title>
    When you decide to create a software application, you should remember that there is no one-size-fits-all solution. The choice should be based on your needs and your customers requirements, the benefits and drawbacks of your choice should be carefully considered. There are a few criteria that can provide the «SaaS vs. regular software application» choice:<br/>
    * For online collaboration solutions for multiple people, SaaS would be a great choice with flexible subscription pricing.
    * For a high-performance product that needs to work independently of external factors, then a standalone program distributed for a fixed fee is a great choice.<br/>
	In this article, we touched on the «SaaS platform vs. regular software application» question, described both types of software in detail and what distinguishes a SaaS platform from regular software applications, as well as we highlighted the benefits and drawbacks of SaaS that can help you make your final decision.<br/>
	We develop web applications and SaaS solutions in particular. If you would like to create a SaaS project or get personal advice on this issue, <a class="link-dark" href="#contact">fill out the form</a> on our website and we will get back to you with the project estimations or answers to your questions.

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In this article, we talk about what distinguishes a SaaS platform from traditional software applications and highlight various examples of products that are suitable for SaaS solutions. If you require any assistance with your project concerning SaaS solutions, feel free to reach out by completing the form on our website.

What Distinguishes a SaaS Platform from Regular Software Applications

<Wrapper emptyHeading backgroundColor="gray">
    <ContentWrapper title="Top 13 Metrics for Assessing Progress in Software Development Effectively">
    We use metrics and measurements everywhere: in research, in marketing or in goods production both physical and digital. Metrics allow people to understand how efficient your company's processes are, and help to make important decisions to improve business operations and productivity. Software developer performance metrics become especially useful in software development using Agile methodology, where you need to monitor the performance and state of the team over time.<br/>
    However, there are so many metrics and parameters that can get lost, and it may not be clear which data is important to analyze and which one is not. Some metrics are needed during development, some are needed before release, and very different data will be needed afterwards. Moreover, not all metrics are appropriate for every product development. You have to select metrics carefully and have a clear understanding of how they relate to business goals which is the most essential.<br/>
    In this article, we look at what software development metrics dashboard can consist of and how it can significantly improve the development team's productivity and help understand the effectiveness of implementing certain solutions and the client satisfaction.<br/>

    <Title className="contentTitle" type="h2" id="software-development-metrics-definition">What is software development metrics</Title>
	Every project task is unique, and a lot of metrics have no value in forecasting if they are not paired up with some business goals. For example, the computational complexity of a product is meaningless if users don't like your software. No matter how cool your product is, all metrics will be worthless without a proper business goal and user orientation.<br/>
    That's why managers focus on specific and subjective software development metrics that are connected to specific features and goals. This allows management to improve their products and improve processes within the company.<br/>
    There are so many things to measure when developing software products:<br/>
    * Software quality and performance;
    * Development team’s effectiveness and progress;
    * Users and developers satisfaction;
    * Product security.<br/>
    Metrics can also help to focus on user experience and product issues and bugs that occur during the product development process. These quantitative metrics allow managers to better understand every aspect of the work:<br/>
    * Finding areas for improvement and fixing the problem as early as possible;
    * Creating a more understandable and accessible product development and maintaining process;
    * Increasing return on investment (ROI);
    * Reducing overtime and lowering development costs across all projects.<br/>

<Title className="contentTitle" type="h2" id="key-metrics">Key software development metrics examples</Title>
	If you choose a remote development team to work with, it is important not to let the project go its own way and control the necessary software development performance metrics, which stimulates the developers to move in the right direction. At the same time, irrelevant metrics will only distract the team from their goals and some important aspects.<br/>
	Different products may have different key metrics for software development, but some of them can be found in most projects. Let's highlight some examples of one of the most important initial metrics to form an understanding of what a metric is and why businesses need it:
    <Img class={['col-12']} width="1981px" height="608px" src="/images/blog/sdm_pic_1.png" alt="Key Software Development Metrics"/>

    * **Time to market** is a product implementation and launching time measurement. Companies try to reduce this indicator, which can provide many advantages, such as engaging a large number of users through relevant and trending functionality.
    * **Development cost.** This is where the total cost of product development is calculated. Obviously, managers strive to reduce this metric to achieve a faster project ROI.
    * **Customer’s satisfaction** shows how satisfied users are with the product. High indicators of satisfaction can be a good sign for long-term cooperation.
    * **Developer’s satisfaction.** This is the same metric as the previous one but for developers, their productivity and motivation level.<br/>

	As we wrote above, there are a lot of metrics to work with. Some of them are completely useless in terms of business goals, like the number of lines of code, working hours or commits made. However, some types of metrics can be very useful. We have identified three large groups, which we will discuss in detail below:<br/>
    * **Agile metrics** for managers to plan the project and optimize development processes.
    * **Technical metrics** required right before release.
    * **Customer metric**s obtained after release.<br/>

    <Title className="contentSubtitle" type="h3" id="agile-metrics">Agile metrics for project managers</Title>
    We will highlight some metrics that will be useful for those who develop software using Agile methodologies. They are not related to the success of product realization and estimation of development costs. These metrics will be useful for development planning and internal process improvement, so that’s why it is important to measure them. In case any of the metrics are out of the range or have a bad trend, it's worth talking to the team to see if there is a cause for concern and whether it needs to be fixed. Let's have a look at some Agile software development metrics.<br/>
        <Img class={['col-12']} width="1981px" height="756px" src="/images/blog/sdm_pic_2.png" alt="Agile Project Management Metrics"/>
        
    <Title className="contentTitle" type="h4" id="release-burnout">Task Completion (Release Burnout)</Title>
    This is a vital metric to measure software development team performance. It shows the number of completed tasks for a sprint or project and how many are left to complete. This is a chart going down that will show how many tasks are currently left and how the sprint is progressing. This metric allows you to monitor the workflow and adjust plans for the next sprints if necessary.<br/>
        Metrics related to task completion can also be seen as the open/closed tasks ratio, where it is important to consider the overall trend, which can show team priorities or issues on the project.

    <Title className="contentTitle" type="h4" id="team-velocity">Development Team Velocity</Title>
	This is a measure of the number of tasks completed in a single period of time, for example, in a sprint. It helps with planning future sprints, however, you should not consider team velocity as well as task completion ratio as a measure of success to compare different developers because the metric is based mostly on subjective assessments.<br/>

    <Title className="contentTitle" type="h4" id="lead-time">Lead Time</Title>
	This metric shows how long it took to implement an idea into a finished software product in total. This metric can help those who want to respond to customer requests more quickly. Teams reduce task fulfillment time by simplifying decision-making processes.<br/>

    <Title className="contentTitle" type="h4" id="cycle-time">Cycle Time</Title>
	This is the time that developers work on each task and functionality, and how quickly they deliver them to production. This metric is included in the Lead Time metric and together form the time to market metric.<br/>

    <Title className="contentTitle" type="h4" id="flow-efficiency">Flow Efficiency</Title>
	This metric measures the ratio of run time to total time, taking into account waiting for tasks to be completed. Waiting occurs when there is insufficient information or resources to implement a feature. One of the manager's tasks is to reduce waiting time in order to optimize the work of the development team, as well as to determine how long tasks are idle and whether it is a problem.<br/>

    <Title className="contentTitle" type="h4" id="developers-satisfaction">Developer’s Satisfaction</Title>
	 <a class="link-dark" target="_blank" href="https://www.recruiter.com/recruitment.html" rel="nofollow">Recruiter.com's research</a> shows that workers who enjoy their work environment are more productive, creative and loyal, and also make more smart and reasonable decisions. Therefore, keeping an eye on employee conditions is one of the most important and challenging tasks for a manager. There are a huge variety of tools for this software developer productivity metric control, but many managers advise starting with the simplest ones if you are just implementing such a metric.<br/>
	A good example of a moodboard was offered by Spotify, which they called <a class="link-dark" target="_blank" href="https://engineering.atspotify.com/2014/09/squad-health-check-model/" rel="nofollow">the Squad Health Check Model</a>. They use two scales: teams (or squads) mark their status in green, yellow, or red for each work aspect, and also mark with arrows whether things are getting better, worse, or staying the same. In this way, managers understand the overall situation and can understand what needs to be done to help a particular team.

    <Title className="contentSubtitle" type="h3" id="technical-metrics">Technical metrics</Title>
	There are several metrics that programmers rely on during program development. It is important for them to achieve a target result by the product release, so don't forget to request this data from your team before the product release.<br/>
	All technical metrics are somehow related to product and service quality, safety, and speed of operations. If we think about quality metrics outside of the technical component, we can include cycle time from Agile metrics, which we covered above, and user satisfaction from customer metrics, which we'll cover a bit later. Since the programming team is also responsible for developing the product, they need to rely on some software development metrics as well. Let's take a look at some of them.
    <Img class={['col-12']} width="1981px" height="608px" src="/images/blog/sdm_pic_3.png" alt="Technical Metrics"/>

    <Title className="contentTitle" type="h4" id="bugs-number">Number of software bugs and defects</Title>
	All developers make mistakes at some point. However, making mistakes cannot be left to happen by itself and needs to be controlled. You can count the number of defects that get into the final product for your development team. It can be normalized and calculated as **defect density** by dividing the number of bugs by the size of the software in terms of function points or user stories (some people count in terms of the number of lines of code). Using several sprints as an example, you can identify the average number of bugs that occur per sprint and then use this data as a basis. Significant deviations from the average values are a serious signal to find out possible problems in development in case of a lot of detected bugs or in testing if too few bugs are detected.<br/>
	Of course, such a value must be regularly updated because developers learn to stop program defects at the development stage. They focus on quality development standards, apply effective testing methods, and, of course, collect and analyze the feedback of their senior teammates to learn from occurring bugs. The latter is most often emphasized as the following metric.

    <Title className="contentTitle" type="h4" id="code-review">Code review feedback</Title>
	This metric is associated with code consistency and quality. Developers must write robust code that will withstand multiple additions and changes to the product. In the beginning, the code will change a lot due to many additions and modifications. But closer to the product launch, such changes should become less. Such metrics allow managers to understand issues related to the structure of the application, programming and testing practices, and the experience of the development team.<br/>
	One important criterion for code quality is **the absence of code duplication**. A high number of code repetitions means a low quality product in terms of run time. Therefore, managers and team leads check code duplication, and for this they can use special services like Sonarqube, which checks code according to the rules of programming standards.

    <Title className="contentTitle" type="h4" id="test-coverage">Test coverage</Title>
	Code test coverage density is the amount of code that has been checked during testing. It allows specialists to determine whether a product has been sufficiently tested before its launch on the market, as well as to understand the risks that some bugs still remain undetected in the program.

    <Title className="contentTitle" type="h4" id="security-metrics">Security metrics</Title>
	Security is an important aspect of software that is often overlooked in the latter stages of development. Security requirements should be simple and reasonable, and the team should keep them in mind and satisfy the metrics that come from those requirements. There are several calculations that will make a big impact to you and your customers:<br/>
    * **Endpoint incidents** – the number of software breaches by a hacker, where the duration of the attack, its severity, and frequency of incidents are taken  into account.
    * **Mean time to recover (MTTR)** – the time between the occurrence of a security issue and the recovery of the program.
	Both metrics should be checked over time, and the smaller they get, the more effective the development team is in finding security bugs in the product and fixing them.<br/>

    <Title className="contentSubtitle" type="h3" id="customer-metrics">Customer metrics</Title>
	Ultimately, any product is created for users. Therefore, the most important indicators for business can be considered their satisfaction from using the software, which is converted into the company's profit as a result. Let's look at the metrics that can be taken into account when analyzing customer and user feedback.
    <Img class={['col-12']} width="1981px" height="455px" src="/images/blog/sdm_pic_4.png" alt="Customer Metrics"/>

    <Title className="contentTitle" type="h4" id="nps">Net Promoter Score (NPS)</Title>
	This metric asks users the question, "How likely are you to recommend a service to your friends?". Users are asked to rate the likelihood on a ten-point scale from "definitely not recommend" (1) to "definitely recommend" (10). The overall NPS score is calculated as the difference between the percentage of positive responses and the percentage of negative responses.<br/>
	This metric allows you to understand how loyal your audience is to you in general and whether they are willing to recommend your services to others.

    <Title className="contentTitle" type="h4" id="csat">Customer Satisfaction Rate (CSAT)</Title>
	This approach is a full-fledged user feedback form that asks users to rate different aspects of the product on any scale the business is comfortable with (either a ten-point scale from NPS rate or a simple "good-bad-neutral" scale). This metric won't answer the question generally, but it will allow you to evaluate the individual parts of your app that users interacted with. This is how you can identify key functionality of your product or evaluate solutions that raise concerns.

    <Title className="contentTitle" type="h4" id="cr">Conversion rate</Title>
	With this metric, you can calculate how many people made the target action you need: for example, subscribed, bought your product, filled out a feedback form and many more.  It is calculated as the percentage of people who took an action out of the total number of users.
	Conversion rate helps to understand how attractive the call-to-action element is for users. And if the conversion rate is low, it is a reason to think about the reasons, which can be problems with marketing, website functioning or product design that prevent users from taking the action you want them to take.<br/>

    <Title className="contentTitle" type="h2" id="ai-healthcare-use-cases-conclusion">Conclusion</Title>

    There are so many software developer performance metrics that can help with the effective implementation of your project. In this text, we described only several popular examples. In fact, there are many more metrics, but it is important to realize that not everything  is suitable for all products. Therefore, if you want to implement the use of metrics in your workflow, you can follow the steps below:<br/>
    * Define your business goals and align your key performance indicators (KPI) with them.
    * Choose the metrics you need that are simple and easy to understand for your managers and team. It is recommended to use the SMART criteria, which tells us that metrics should be specific, measurable, achievable, relevant and time-bound.
    * Update key metrics regularly to stay relevant as your product evolves
    * Use tools you are comfortable with, like Trello or Jira to visualize your metrics.
    * Encourage a team that is doing their part to improve the continuous development process.<br/>
    In this article, we took an in-depth look at the main types of performance metrics for software developers and explored why metrics are important for business and why they should be aligned with business goals.
    Since using software development metrics is a complicated process for beginners, when working with a development team (in-house or remote), it's hard for a startup and business to develop their product without an experienced project manager. So if you want to hire a development team with a project manager who can take care of tracking multiple performance metrics, feel free to <a class="link-dark" href="#contact">write to us</a> about your project. We will be happy to answer all your questions or send you an estimation of your project.

    <AuthorInfo image="/images/authors/4.jpg"
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Victoria Shaduro, Client Success Manager

It's crucial to figure out if your project is on the right path and make any necessary adjustments. In this article, we share the top 13 software development metrics for evaluating your project's efficiency independently. If you have any questions about your project assessment, feel free to reach out to discuss it further.

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<Wrapper emptyHeading backgroundColor="gray">
    <ContentWrapper title="AI Use Cases in Healthcare and Trends for 2024">
        In recent years, fields related to artificial intelligence (AI) developed rapidly and played an important role in many industries. At the same time, the field of healthcare actively developed and this was boosted by the integration of advanced digital technologies.<br/>
        Medicine is now facing increasing patient demand and needs due to the effects of an aging population, multiple chronic diseases and their complicated methods of treating,  increased public health awareness and many more. As a result, healthcare systems will have to deal with a huge number of people with complex needs, i.e. they will have to process a large amount of data. AI in healthcare use cases can come in handy: it can increase the productivity of doctors and efficiency of medical care, as well as optimize many administrative processes. <a class="link-dark" target="_blank" href="https://www.accenture.com/au-en/insights/health/artificial-intelligence-healthcare" rel="nofollow">Accenture</a> estimates that AI tools could save the healthcare system about $150 billion a year by 2026, and according to <a class="link-dark" target="_blank" href="https://www.statista.com/topics/10011/ai-in-healthcare/#topicOverview" rel="nofollow">Statista</a>, the global healthcare AI market will reach $188 billion by 2030.<br/>
        However, it is important to realize that medical data is sensitive in terms of privacy and accuracy of analysis, which means that the software must be strictly regulated according to the quality requirement and country laws.<br/>
        In this article, we look at some general trends in AI development, the challenges of its implementation in medicine, as well as review some popular examples of AI use cases in healthcare.

        <Title className="contentTitle" type="h2" id="ai-healthcare-trends">The rise of AI and top 3 AI trends</Title>
	AI-related fields are reviving and getting better at the moment thanks to the development of cloud computing and big data analytics algorithms. AI tools learn from a big bunch of examples, so they can make precise predictions, and cloud technologies allow large AI applications to be run in one place without the need for complex infrastructure deployment.<br/>
We can distinguish three varieties among all the AI directions that will be relevant in the near future in general, not only in healthcare.
        <Img class={['col-12']} width="1981px" height="608px" src="/images/blog/ai_healthcare_pic_1.png" alt="Top 3 AI Trends in Healthcare"/>

        <Title className="contentSubtitle" type="h3" id="auto-ml">Automated Machine Learning (AutoML)</Title>
        	It is a technology where machine learning (ML) algorithms are used for specific data. ML tools make decisions, set up and optimize models, and perform time-consuming and repetitive tasks independently. AI & ML use cases in healthcare will have great potential, for example, in making diagnosis based on a large amount of data or in solving the reverse problem, where the system knows the diagnosis and tries to investigate the associated signs of disease. AutoML will also be useful for people in the field of economics and commerce.<br/>

        <Title className="contentSubtitle" type="h3" id="generative-ai">Generative AI</Title>
	The most popular field of the last two years. We think that almost everyone heard about tools like ChatGPT, Midjourney, Jasper.AI, Google Bard and many others. All these generative AI based tools are used to perform all sorts of tasks with instructions.  It uses the available data to create a whole new multimedia unit: an image, video, sound or different kinds of text (both human languages and computer code).<br/>
	Generative AI found its application in marketing and creative purposes, which has led many media businesses to think about regulating these tools. However, it is too early to use generative AI in medicine because the neural network is trained on a large amount of data and does not know what is true and what is false, and the generated data can lead to fatal consequences.<br/>

    <Title className="contentSubtitle" type="h3" id="nlp">Natural Language Processing (NLP) AI</Title>
	NLP is a type of artificial intelligence that analyzes, understands, and processes spoken or written human language. Over time, natural language processing based tools are predicted to increase in number, where user interaction will be more intuitive. This type includes the previously mentioned chatbots like ChatGPT and Midjourney, as well as voice assistants from Google, Apple and Amazon.<br/>
	NLP tools can help doctors in their work by being able to detect and highlight some important information and attributes that, for example, can help the doctor quickly make an accurate diagnosis and prescribe effective treatment.<br/>
    
    <Title className="contentTitle" type="h2" id="ai-healthcare-challenges">Challenges in AI implementation in healthcare</Title>
	AI-based tools have amazing capabilities and can significantly change the work of healthcare professionals for the better, however, there are many legislative, technical and medical research limitations that prevent the mass use cases of AI in healthcare.<br/>
    * **Lack of high-quality medical information.** A huge amount of high quality data is required to train neural networks properly. Patient medical data is highly fragmented and sometimes data from different medical organizations is highly inconvenient to share, it becomes difficult to collect it for training and testing AI algorithms. The healthcare system needs to focus on creating medical data standards for this so that they can be used not only for training medical neural networks, but also for more seamless automated work between healthcare organizations.<br/>
    * **Legal regulations.** Currently, there are several regulations on the storage, collection, and processing of patient personal data. The main laws are the U.S. Health Insurance Portability and Accountability Act (<a class="link-dark" target="_blank" href="https://www.hhs.gov/hipaa/index.html" rel="nofollow">HIPAA</a>) and the European General Data Protection Regulation (<a class="link-dark" target="_blank" href="https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A02016R0679-20160504" rel="nofollow">GDPR</a>), which protect patient personal data in the U.S. and EU. Of course, these laws came about when artificial intelligence was in its early stages of development (in 1996 and 2018, respectively), but policymakers have recently proposed new laws to regulate AI's handling of high-risk information like medical information. In 2021, the European Commission began work on regulating AI in the EU and issued <a class="link-dark" target="_blank" href="https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex%3A52021PC0206" rel="nofollow">a Proposal for a Regulation of the European Parliament and of the Council establishing harmonized rules on AI</a>, which will form the basis of a future AI law. According to this proposal, transparency will be one of the main requirements for AI to work with medical data, which is a fundamental problem for such tools.<br/>
    * **AI tools transparency.** This is a well-known paradox associated with black-box algorithms, which suggests that additional information about AI-based tools has both significant benefits and serious threats. On the one hand, transparency will reduce negative ethical and social consequences, reduce algorithm bias, and increase trust in AI results. But on the other hand, revealing information about tools will make them more vulnerable to attackers and increase the chances of stealing the algorithms of some AI tools that are not open source software. To minimize the negative effects of this paradox, important steps need to be taken in regulating AI and the distribution and protection of information.<br/>
    * **Weaknesses in methodological research.** Almost all research related to AI in medicine is based on recorded facts about patients. For AI tools to truly provide accurate answers, you need data from prospective studies, i.e. working with current patients in real time using checkups and monitoring with sensors and trackers.<br/>

    <Title className="contentTitle" type="h2" id="ai-healthcare-examples">Examples of AI use in healthcare</Title>
	The potential for implementing artificial intelligence in medicine is very big. Algorithms based on the analysis of big pieces of medical data allow for more accurate diagnosis and detection of complex diseases. Unfortunately, the introduction of AI is not so obvious to patients, and many of them do not believe that it will affect the outcome of their treatment for the better. To understand how AI & ML use cases in healthcare, let's look at some impressive examples of how artificial intelligence can improve the work of doctors.<br/>

        <Img class={['col-12']} width="1981px" height="608px" src="/images/blog/ai_healthcare_pic_2.png" alt="Examples of Use AI in Healthcare"/>

    <Title className="contentSubtitle" type="h3" id="medical-image-analysis">Medical image analysis and recognition</Title>
	Each of us has a lot of checkups every year, and some of their results are presented graphically: MRI and ultrasound screening, ECG results, X-rays and CT scans. In order to process and group them, a doctor can spend a huge amount of effort and time.<br/>
	This is where artificial intelligence comes to the aid of cardiologists, radiologists and other doctors, which allows them to quickly analyze a large amount of data, make a more accurate diagnosis and choose the most appropriate method of treatment. With the help of artificial intelligence, it is possible to more accurately find tumors on MRI scans, detect Alzheimer's disease during brain screening, find problems in the human bone system and prevent possible bone fractures.<br/>

    <Title className="contentSubtitle" type="h3" id="unstructed-health-reports-analysis">Analysis of unstructured health records and treatment selection</Title>
	Artificial intelligence is not only able to analyze patients' graphical data, but it can also analyze their electronic medical records (EMR), which often contain unstructured but very useful information for doctors that helps prescribe effective treatment: the patient's medical history, lifestyle, or genetic information. All this allows the right drug to be selected, especially when making a mistake can be fatal, like in the treatment of complications of diabetes, cancer, or brain and heart diseases.<br/>
	AI also enables real-time monitoring of patients and tracking of vital parameters, so that doctors can detect disease at an early stage, start treatment and prevent possible complications.<br/>

    <Title className="contentSubtitle" type="h3" id="telemedicine-and-chatbots">Telemedicine and medical chatbots</Title>
    Generative AI use cases in healthcare are one of the top trends in 2024 and this technology has many advantages:<br/>
    * A lot of patients with mild illnesses and those living in small, remote communities can be served with telemedicine.
    * Telemedicine helps doctors diagnose patients more quickly because they have many AI and ML-based tools at their disposal to analyze and recognize symptoms of illness.
    * Patients can get quick personalized advice about their health in chatbots: they can monitor their health states, learn about medications and their possible side effects, and get recommendations for symptomatic treatment.
    * Patients can easily make an appointment with a doctor and prepare all the necessary information for further treatment in the hospital with the help of these technologies.<br/>

    <Title className="contentSubtitle" type="h3" id="drugs-research">Drugs research & development</Title>
	Fast-track drug and vaccine development became insanely relevant in the days of COVID-19, when viruses needed to be studied, vaccines had to be clinically tested, and released into production very quickly. Previously, such research was done by trial and error and could <a class="link-dark" target="_blank" href="https://www.beckershospitalreview.com/innovation/how-ai-can-speed-up-drug-development.html" rel="nofollow">take years or even decades and cost billions of dollars</a>. Artificial intelligence significantly reduced the cost and production time by a factor of ten: from decades to months and from billions of dollars to thousands of dollars. AI tools analyze existing drugs and suggest options on how they can be improved to treat diseases more effectively or how they can be modified to treat other diseases. Refining old drugs has proven to be a cheaper process than creating new ones.<br/>
    AI can help bring new drugs to market much faster, which could help save <a class="link-dark" target="_blank" href="https://www.policymed.com/2014/12/a-tough-road-cost-to-develop-one-new-drug-is-26-billion-approval-rate-for-drugs-entering-clinical-de.html" rel="nofollow">up to $2.6 billion</a> in drug development costs.<br/>

    <Title className="contentTitle" type="h2" id="ai-healthcare-companies">Companies adopting AI in healthcare</Title>
	Despite technological and legal challenges, some companies have been able to successfully integrate their AI-based tools into the healthcare system. The tools presented below have been developed for a specific group of tasks and diseases, such as recognizing and treating diabetes, heart disease, kidney disease, and eye disease. We will highlight a few companies and research labs that have developed their methods and programs for AI in healthcare use cases.<br/>

    <Title className="contentSubtitle" type="h3" id="google-deepmind">Google DeepMind</Title>
	Google DeepMind is a research lab that studies and develops AI solutions. One of the studies was related to the treatment of patients with kidney disease and predicting the treatment of patients in intensive care. The system is based on deep learning technologies that are used to analyze large amounts of medical data to offer patients individualized treatment plans.<br/>

    <Title className="contentSubtitle" type="h3" id="merative">Merative (ex. IBM Watson Health) </Title>
	Merative (ex. IBM Watson Health) is a company that creates medical software based on AI, NLP, ML and big data analytics. Their medical technology helps doctors in creating treatment plans for cancer patients, as well as detecting diseases at the earliest stages.<br/>

    <Title className="contentSubtitle" type="h3" id="alivecor">AliveCor</Title>
	AliveCor specializes in building deep learning based tools for diagnosing and creating treatment plans for heart disease. They make software to analyze electrocardiograms and also develop hardware to monitor heart health. They were the first company to be authorized to create their own medical band for Apple Watch called KardiaBand that can detect atrial fibrillation, the first cause of stroke.<br/>

    <Title className="contentSubtitle" type="h3" id="idx">IDx</Title>
	IDx-DR is the world's first autonomous diagnostic system for the detection of diabetic retinopathy, a severe complication of diabetes mellitus. The retinal analysis is based on deep learning and the screening results are autonomous so they do not require a physician's description, which allows for screening as part of routine hospital visits.<br/>

        <Title className="contentTitle" type="h2" id="ai-healthcare-use-cases-conclusion">Conclusion</Title>
	AI use cases in healthcare can change the way to treat people in many ways:<br/>
    * It will significantly improve the accuracy of diagnoses
    * It will make medicine more accessible to patients
    * It will make medical data more understandable and easier to work with<br/>

    Such healthcare progress is hindered by the high cost of implementing and developing new technological products, as well as people's distrust about the use of artificial intelligence in sensitive industries like medicine. Another important reason for the slow AI-technology implementation in medicine is the problem with data processing and interpretation. Most companies and startups are now focused not on creating programs and training AI models, but on collecting user data and structuring it so they can train models on it in the future and create their own products when someone develops effective AI-algorithms especially for healthcare.<br/>
    However, even now the potential benefits of AI use cases in healthcare are beginning to outweigh the fears and drawbacks, people will change their perceptions of AI, and eventually the technologies of tomorrow will be available to everyone. And one would like to believe that AI in healthcare use cases will help us live long and happy lives.<br/>
        Medicine and healthcare are just one of the industries where AI-based technologies can be successfully introduced. In other fields, such as art, media and entertainment, AI is also applied to many projects. However, it is important to realize that you should approach the issue of implementing AI in your products responsibly. So if you want to use AI solutions in your business, feel free to <a class="link-dark" href="#contact">contact us</a> and we will be happy to tell you how to implement AI solutions in the most effective way. 

        <AuthorInfo image="/images/authors/1.jpg"
                    link="/authors/alexander-gurov"
                    about="Alexander has been a part of the team since 2013 and is deeply interested in building top-notch web development products."
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Explore the significant trend of AI that has emerged in recent years, with increasing integration into various fields, particularly in healthcare. This article delves into the diverse use cases of AI in the healthcare sector and sheds light on potential trends anticipated for the year 2024. If you're interested in discussing the application of AI to your project, feel free to reach out to us.

AI Use Cases in Healthcare and Trends for 2024

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<Wrapper emptyHeading backgroundColor="gray">
    <ContentWrapper title="12 Types in Software Development: A Comprehensive Guide to Discovering the Best Resources for Your Product Development">
        At the beginning of the 21st century, the world has progressed rapidly, resulting in the emergence of various technologies that have become an integral part of our daily lives. To enter the market, you need to create your own product that fulfills your goals: it could be a website or an application for a mobile, computer/laptop, wearables or any other device. Each type of product requires different sets of skills and ways of developing, so you may need different types of software developers working together as a team to bring the product to life.<br/>
        In this article we find out what software development is, and what types of software development exist. Of course, there is no single classification or terminology, but there are many points of agreement. We'll take a look at 12 types of software developers: the «timeless classics» and the «new to the market» due to current technologies and development trends.

        <Title className="contentTitle" type="h2" id="software-development-definition">What is a software development?</Title>
        Software development is about creating a special type of application for specific devices or platforms. Despite the great number of development methodologies, including Agile methodologies, that we discussed in previous materials, it contains similar steps that are repeated at regular intervals: designing, coding, testing, fixing bugs, implementing new features and supporting.

        <Title className="contentTitle" type="h2" id="12-types-of-software-development">12 types of software developers</Title>

        There are many classifications of software development. Some experts divide them by development side, type of platform or even employed technologies. We use all three factors and present 12 types of developers based on that.

        <Title className="contentSubtitle" type="h3" id="development-tier">Types of software development based on development tiers</Title>
        Almost every software can be divided into three parts: the user-interacting part, the server part and connections between them. Front-end developers are responsible for the first part, back-end developers work on the second one and API developers build the bridges between front-end and back-end. That's why working with a team consisting of different types of developers is a great choice. Let's look at each type separately.

        <Img class={['col-12']} width="1981px" height="582px" src="/images/blog/types_of_developers_pic_1.png" alt="Types of Software Developers Based On Development Tier"/>

        <Title type="h4" id="front-end">Front-end developers</Title>
        When you look at the interface of the software, you see the front-end developers work. They are focused only on creating UI and human-interface interaction, fixing bugs and checking if the user interface works correctly on different platforms. Front-end developers should collaborate with back-end ones to create a complete software where all product parts work in harmony.<br/>
        There are essential technologies for web development such as HTML, CSS and its frameworks, JavaScript which allow to create a web interface foundation. Also some advanced JavaScript frameworks, such as ReactJS, Vue.js and Angular, help to make more complex interfaces including ones with business logic. There are other technologies that are used in mobile development, and we will get to those a little bit later.

        <Title type="h4" id="api">API developers</Title>
        This type of developers help to build the bridges between the external visual interface of a product to its server part. They write non-UI code that executes in a front-end part and also interacts with functions running on the server.<br/>
        The API also allows one software solution to communicate with others. For example, APIs help open up map services as soon as you enter an address in the Google or Yahoo search bar or listen to a song on Apple Music or Spotify once you find it on Shazam.

        <Title type="h4" id="back-end">Back-end developers</Title>
        As you understand, front-end developers create the user interface, while the back-end developers deal with the implementation of the server part of the application. The back-end part includes server settings, applications and databases that are designed by developers. They create the functional core of the product, closely paying attention to system integration, its basic logic and user information processing. Back-end developers can also be involved in API integration, that’s why there are no engineers who work only with APIs.<br/>
        The performance of your product directly depends on the stability of the server part of it and your software fails regularly, it may be a problem with the backend. Moreover, the data should be properly handled in the system as it’s quite important for user protection and overall performance of the product.<br/>
        Some of <a class="link-dark" target="_blank" href="https://www.statista.com/statistics/793628/worldwide-developer-survey-most-used-languages/" rel="nofollow">the essential back-end technologies in 2023</a> are JavaScript (and Node.js framework, in particular), Python, Java, PHP and Ruby (for example, Ruby On Rails framework).

        <Title type="h4" id="full-stack">Full Stack developers</Title>
        Full Stack developers combine abilities of both worlds: front-end and back-end. These developers can work on all aspects of the product: creating user and server parts, combining them through API and testing it.<br/>

        <Title className="contentSubtitle" type="h3" id="platform">Types of software development based on the type of platform</Title>
        To develop a product for each platform, you need separate development teams and significantly different development tools. Let’s look at the several popular types of development and understand why you should choose one platform or the other.

        <Img class={['col-12']} width="1981px" height="582px" src="/images/blog/types_of_developers_pic_2.png" alt="Types of Software Developers Based On Type Of Platform"/>

        <Title type="h4" id="web">Web developers</Title>
        Web developers make applications that can be accessed through the browser on any device connected to the Internet. Web development includes the following parts: making front-end and back-end parts of the product and their maintenance. So the previous classification of developers types fully describes what web development consists of.<br/>
        Why should businesses choose web development?
        * A web application is available anywhere on any device connected to the Internet. There is no need to install the app on the customer's device.
        * Modern web can be easily adapted and updated to the changing needs of the customer and expanded as users increase.
        * Web applications are flexible enough to serve a wide variety of customers and offer personalized services.
        * Compared to traditional software, web applications are more convenient, easy and inexpensive to update. That means it can help you reduce the development cost.

        <Title type="h4" id="desktop">Desktop developers</Title>
        Desktop developers create applications that run locally on computers or laptops with or without an internet connection. They run on Windows, MacOS and Linux operating systems. If you've ever worked with products from the Microsoft Office family, then you probably understand what desktop applications are. Desktop developers use programming languages like C#, Swift, Objective C, Java, C++ and some others.<br/>
        Desktop apps were the main type of software 20 years ago, but due to the massive spread of portable devices like smartphones, tablets and wearables in the 2010s, the development vector has shifted towards them and desktop development has become less common. One of the current development trends is the shift to Cloud technology, whichalso reduces the popularity of desktop development. But a lot of customers still use desktop apps everyday for the following reasons:
        * Some companies offer their services offline, without the need for an internet connection or access from all devices. That's why desktop development is ideal for them.
        * Desktop apps can provide a higher level of security than web applications because they are installed locally on the user's device. Also some applications can encrypt user data, making it difficult for hackers to access confidential information.
        * Desktop applications can use some features of the device such as ability to access the file system or use the camera or microphone. This level of access is not possible for web applications.

        <Title type="h4" id="mobile">Mobile developers</Title>
        Mobile developers work with apps for mobile operating systems like Android and iOS. Most of them use an internet connection like Instagram that uses it to download content or Notes that can be edited from all devices. However, some companies offer offline functionality – for example, some games can be played without the Internet.<br/>
        Nowadays almost every business is transitioning to providing digital services and their needs for mobile app development are growing every year. Companies develop their own apps for each platform or create cross-platform solutions. The last one relies on a single set of tools to make applications compatible on all platforms. However, a lot of experts agree that making separate apps for every platform is more effective than cross-platform solutions.<br/>
        Native app development uses a completely different set of tools from web development: Java or Kotlin languages for Android and Swift for iOS. Because of the strong differences in technology, companies hire multiple development teams to create a product for multiple platforms.<br/>
        Many companies prefer mobile app development as an effective channel for communication with customers for the following reasons:
        * Communication through mobile apps saves the user time because all the necessary functionality is already built into the product. For example payment functions in the app. <a class="link-dark" target="_blank" href="https://www.zensar.com/sites/default/files/white_papers/Payments_Industry_Revolution_and_Key_Emerging_Trends.pdf" rel="nofollow">Zensar research</a> shows that the number of payments for mobile apps has grown from 41.8% in 2019 to 52.2% in 2023.
        * The mobile app is a great marketing channel. With interactive elements users can customize recommendations for products and services they can use. This thing can help increase brand recognition.
        * Mobile apps are convenient for implementing technological trends like IoT. You can incorporate your services into other devices and provide new functionality to your customers.

        <Title className="contentSubtitle" type="h3" id="technologies">Types of software development based on technologies involved</Title>
        Companies should always pay attention to external factors: the current situation on the market, tech news and breakthrough tools. Technological trends often help Executives choose new development strategies and implement new technologies. We will look at several types of developers that have appeared because of current software development trends.

        <Img class={['col-12']} width="1981px" height="582px" src="/images/blog/types_of_developers_pic_3.png" alt="Types of Software Developers Based On Technologies Involved"/>

        <Title type="h4" id="cloud">Cloud developers</Title>
        In 2022 cloud technologies became an essential part not for startups and small businesses, but also for big companies. Using cloud technologies became one of the most remarkable trends in recent times because the transition to this technology is very easy. Google, Amazon, Microsoft and other big corporations presented technology and offered their services to other businesses. There are several examples of cloud technologies such as Dropbox, Google Drive, GitHub and many more.<br/>
        Nowadays businesses are interested and looking for professionals who can work with cloud technologies because of the ease and flexibility of deploying this technology. Their task is to create applications and programs that will be stored on a remote server, not on local storage. The cloud developer sets up architectures using Cloud providers like AWS (Amazon Web Services), Google Cloud, Microsoft Azure and many others, and also manages security and access to the system. The developer must know Java, JavaScript, Python, Go and other back-end languages.

        <Title type="h4" id="vr-ar">VR/AR developers</Title>
        Virtual, augmented and mixed reality have been predicted as a technological trend many years ago. In recent years these technologies have evolved rapidly. According to <a class="link-dark" target="_blank" href="https://www.statista.com/statistics/591181/global-augmented-virtual-reality-market-size/" rel="nofollow">Statista</a>, the VR, AR and MR market will be worth $250 billion by 2028.<br/>
        VR technologies are being implemented in social aspects, like healthcare, transport, education and many more. Also the announcements of new VR/AR devices, like Apple Vision Pro, the most recent and the most notorious one, are raising stakes and giving new hopes for further development. So VR/AR software development may become in demand.

        <Title className="contentSubtitle" type="h3" id="technologies">Types of data-related software development</Title>
        Big companies collect huge amounts of data to analyze their customers, their behavior to identify trends and improve the product. This way companies can reduce the action-response time which is important for predicting further user interaction scenario. Businesses hire different types of Data engineers to collect, store and move the data, build models from it, analyze it and many more. The following types of developers have a lot of similarities but also have some differences that we describe further.

        <Img class={['col-12']} width="1981px" height="582px" src="/images/blog/types_of_developers_pic_4.png" alt="Types of Data-Realted Software Development"/>

        <Title type="h4" id="big-data">Bid Data engineers</Title>
        Big Data engineers are able to help set up analytic tools and systems for very big amounts of data. They create programs to store and retrieve large amounts of data in many types of systems such as data storages, ETL systems or relational databases. Developers should know frameworks and systems for distributed big data storage and processing such as MapReduce, Hadoop or Spark as well as with SQL, Java, Python and R languages.<br/>

        <Title type="h4" id="data-science">Data Science engineers</Title>
        Data science is a broad term that is used for scientific methods of extracting knowledge from data. It combines computer science, mathematics, and business logic. Data science developers apply their knowledge in creating software to analyze data sets and build mathematical models based on that analysis to predict product potential. As you understand, this is a software for inner use in companies. Developers use Python and R languages and knowledge of linear algebra and multivariate computing.<br/>
        Data Science is one of the fastest-growing areas, and this trend becomes more evident every year as new technologies emerge, such as artificial intelligence and neural networks, which we'll talk about a little later.

        <Title type="h4" id="ai-engineers">AI engineers</Title>
        We think the following fact is obvious: Artificial Intelligence is the number 1 trend in 2023. AI-based tools like ChatGPT, Midjourney, Copilot, or Orchard have impressed everyone with their potential. While previously everyone was sure that this technology had no risks for artists, musicians, writers, designers and developers, now the community is talking about these risks with more concern. We will talk about how to use ChatGPT in programming and whether it will kill the development profession in the following articles.<br/>
        AI developers specialize in making products and applications based on artificial intelligence. They work on algorithms for machine learning, natural language processing, computer vision and others. AI developers use Python, R, Java and C++, and use frameworks and libraries such as TensorFlow, PyTorch, and Scikit-Learn to design, train, test and deploy complex models. In addition AI developers actively collaborate with Big Data engineers who help with the big data processing and analysis that is required to build effective models.


        <Title className="contentSubtitle" type="h2" id="developers-type-conclusion">Conclusion</Title>
        In this article we discussed different software development type classifications. This is not an exhaustive list of all types of software developers as it is important to remember that your needs will change, and over time you will look for different types of software developers. However, two things should remain unchanged: determining the requirements and carefully researching the professionals you want to hire.<br/>
        You probably found in this article some types of software developers to hire, or you didn’t and need some advice. In both cases, feel free to <a class="link-dark" href="#contact">contact us</a> with your ideas and questions and we will be happy to help you with the implementation of different types of software developers in your project or help you figure out what suits you best.

        <AuthorInfo image="/images/authors/1.jpg"
                    link="/authors/alexander-gurov"
                    about="Alexander has been a part of the team since 2013 and is deeply interested in building top-notch web development products."
                    socialLinks={[
                        { link: "https://www.linkedin.com/in/a-gurov/", icon: "linkedInIcon" }
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12 Types in Software Development: A Comprehensive Guide to Discovering the Best Resources for Your Product Development

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  <ContentWrapper title="Can ChatGPT Write Code? Let's Experiment to See If It Can Replace Developers Completely">
    It seems that literally everyone has heard about artificial intelligence over the past year, it became an integral part of our lives and many companies are integrating AI tools into their software products. The names ChatGPT and Midjourney have already become common nouns, as AI is the number one trend in 2023.<br/>
    Until the end of 2022, everyone was assured that these technologies had no risk for creative and intellectual occupations. However, current AI capabilities seem so shocking, that everyone has expressed their fears at some point. The results of AI graphic and musical activities are beginning to be regulated by laws. But what about software development? Will developers lose their jobs because of neural engines? Well, in a nutshell, they will not, but their work will change significantly.<br/>
    In this article we did an experiment and tried to create a Google Chrome extension using ChatGPT to answer whether ChatGPT can write code, how good it is at generating code, what will happen to software development and how ChatGPT can be useful in development.
    
    <Title className="contentTitle" type="h2" id="chat-gpt-definition">What is ChatGPT?</Title>

	ChatGPT is a natural language processing algorithm from OpenAI, based on artificial intelligence technology, that allows users to communicate with the chatbot as if it was a real person. The AI model was trained by Reinforcement Learning from Human Feedback (RLHF). <br/>
	The ChatGPT developers <a class="link-dark" target="_blank" href="https://openai.com/blog/chatgpt" rel="nofollow">discussed</a> some limitations of the tool:
    * ChatGPT writes responses that appear to be true in some cases, but they are all fake, and this task is difficult for the following reasons:
      * Reinforcement learning (RL) does not involve outwardly indicating truth and falsehood.
      * Forcing the model to be cautious is a bad idea, because that way it may not answer questions to which it knows the answers.
      * The neural network's answer depends on the knowledge base on which it was trained, not on the knowledge of a particular person, so controlling the model's training can lead to strange results.
    * ChatGPT is sensitive to changes in query wording or repeated attempts to enter the same query. For example, the model may not know the answer to a question, but with a small change it will be able to give the correct answer.
    * Very often the model is verbose and uses many cliched phrases due to the fact that it was important to the AI-instructors that the neural network give long and exhaustive answers, as well as known over-optimization problems. 
    * The perfect scenario for a neural network to work with a user is to ask clarifying questions of the user to form the most accurate answer. However, at the moment, algorithms try to guess the context implied by the user.
    * During the training of ChatGPT, much effort was put into ensuring that the model refuses to respond to inappropriate queries and harmful instructions. However, it continues to respond to them in a biased manner because controlled learning is bad for the algorithm. To address this problem, OpenAI uses a moderating API that allows it to warn users of unsafe content as well as block it. However, at the moment, OpenAI developers expect such protection to have false alarms.

    <Title className="contentTitle" type="h2" id="how-to-write-code">How to get ChatGPT to write code?</Title>
    
    * **Using OpenAI’s chatbot directly.** OpenAI created a website and mobile apps where users can write prompts to the neural network: you can choose your preferable language, define the role that chatbot would do, make necessary requirements and tasks, and also ask for detecting and fixing errors in code. You can get direct access to it on the OpenAI website as well as through the iOS app. This is the method we use for this article.
    * **GitHub Copilot X.** In 2023 GitHub partnered with OpenAI to launch the GitHub Copilot X tool, which allows you to write code directly into GitHub. It works on the GPT-4 model, which is the most powerful model at the moment, and can write entire functions, explain code in natural language, fix bugs, write unit tests for code fragments and many other things that were shown in <a class="link-dark" target="_blank" href="https://www.youtube.com/watch?v=4RfD5JiXt3A" rel="nofollow">the Copilot X announcement</a>. Copilot is also available as an IDE extension for Visual Studio, VS Code, JetBrains IDE and others. Some professionals think that using GitHub Copilot X is more suitable than usual ChatGPT, because it is made specifically for software development and programming.
    * **CodeGPT** is an extension for VS Code IDE using ChatGPT to write code, in particular GPT-3.5 and GPT-4 (this requires API access). Like Copilot X, it makes code on demand, explains code snippets, does refactoring and compiles documentation. In general, it can handle everyday tasks.

    <Title className="contentTitle" type="h2" id="benefits">Experiment with using ChatGPT to write code</Title>

    ChatGPT is a powerful tool that is used in many different areas. We wanted to understand how to write code with ChatGPT, and how well it handles this, so we conducted an experiment and tried to create a simple extension for Google Chrome browser. At that time, the newest version ChatGPT (GPT-4) was already out, and it was interesting to see its attempts at writing code.

    <Title className="contentSubtitle" type="h3" id="prompt">Initial prompt</Title>
    The first thing we did is to set the context for ChatGPT: we defined a role for the neural network, which it should perform, and described the task to complete. We wanted to create a simple browser extension to manage several kinds of tasks: work, personal and recurring. We also set the interface layout, namely where each block of tasks should be placed, and we described the extension functionality, such as creating, editing and deleting tasks. Finally, the initial prompt looked like this:

    <Img class={['col-12']} width="1561px" height="796px" src="/images/blog/can_chatgpt_write_code_pic_1.png" alt="ChatGPT Initial Prompt"/>

    As a result, ChatGPT wrote HTML and CSS code for the extension. We were not particularly surprised by this, because this is not our first AI-using project to use AI, but the code worked and that was good. The neural network also created  the manifest.json file for us, which contained the technical and common descriptions of the extension, version number and permissions. This is a necessary file for the extension to work, but developers  are usually not that keen on  making tech documentation.<br/>
	At that moment, the chatbot helped us with one of the problems that often occurs at the beginning of work on different projects – the «blank slate» problem. Beginner developers don’t know where to start very often and spend a long time trying to figure out how to make the initial version of the product work. Sometimes even experienced developers have this kind of problem, and ChatGPT usually does a great job.<br/>
	At this point the result looks like this:

    <Img class={['col-12']} width="1561px" height="796px" src="/images/blog/can_chatgpt_write_code_pic_2.png" alt="ChatGPT First Results"/>

    <Title className="contentSubtitle" type="h3" id="feature-development">Feature development</Title>
	Despite the fact that at the very beginning ChatGPT produced HTML and CSS code, the neural network did not generate JS code that processes events, so the requested functionality was missing. ChatGPT was probably interrupted by running out of a certain amount of tokens or symbols and we should have asked to continue the generating process and then we would have received the missing piece of code.<br/>
    After several attempts we started to fix bugs with ChatGPT and provide a more detailed description of the required functionality. GPT-4 was carefully correcting and supplementing the code, and after some iterations we finally got the code that worked decently.<br/>
    While ChatGPT was creating JS code for us, we also found out that the accuracy and detail of the prompt is essential from the very beginning. Accurate queries help you spend less time generating code that meets your goals.<br/>
    As a result, we got a simply designed Google Chrome extension, where users can add, delete and edit work, personal and recurring tasks and mark them if they are done. However, there are some problems that are impossible using ChatGPT as a full replacement of developers.


    <Title className="contentSubtitle" type="h3" id="chat-gpt-challenges">Challenges in working with ChatGPT</Title>
	While working with ChatGPT, we noticed several important points that are worth considering in the future.

    <Title type="h4" id="code-quality">Code quality</Title>
    The quality of the initial solutions that GPT-4 offered was comparable to the level of a diligent first-year programming student: the entities were weakly dependent on abstractions, which meant that one of the main Object-Oriented Programming Concepts was not followed properly, and there was a lot of repetition in the code.<br/> 
    ChatGPT wrote code for an extension that locally saved an HTML code with tasks, buttons, and other design elements, which is an unwise decision. A neural network did it as straightforwardly as possible, even though there are better trivial solutions like saving tasks in a json file.

    <Img class={['col-12']} width="1561px" height="796px" src="/images/blog/can_chatgpt_write_code_pic_3.png" alt="ChatGPT JSON File"/>

    However, if you ask ChatGPT to rewrite code in another way, it would do it properly. Moreover, we noticed different levels of quality of generated code when we were using neural networks in other programming tasks. Perhaps the model was trained on an uneven dataset and there were no good examples of code for some tasks.<br/>
    At this point GitHub Copilot X probably would have performed better because it is designed specifically for programming. Nevertheless, GPT-4, a non-specialized tool, did a pretty good job.

    <Title type="h4" id="interface">Interface description</Title>
    There is an assumption that neural networks don’t have so many examples of linking a verbal description of the software interface to generating code. That’s why making prompts for creating code for complex interface structures is a bad idea. For this purpose, it would be more efficient to use the capabilities of Figma which has recently launched a «developer mode» in beta testing that allows you to create interfaces and get accurate CSS code.

    <Title type="h4" id="context-loss">Context loss with a neural network</Title>
    Problems with the interface didn’t end here. When we got the necessary functionality, we decided to work on the front-end of the extension. This is where the biggest disappointment awaited using ChatGPT to write code. When asked to make the design a little different, the neural network generated new HTML code but didn’t link it to the existing JS code. Fixing bugs started a total disaster. Probably at some point ChatGPT lost context of the conversation and didn’t use the initial requirements to generate new versions of code. When we tried to fix one problem, the neural network made others. And it kept going in a circle.<br/>
	At some point editing code in this way became a torture, so we asked the neural network to output the entire code with all previous requirements we made. It provided a code with a totally different structure without our requirements. As a result, we did the final result by ourselves based on the generated results.

    <Title className="contentSubtitle" type="h3" id="chatgpt-results">Results</Title>
	After four evenings of work, we came up with this result:

    <Img class={['col-12']} width="1561px" height="796px" src="/images/blog/can_chatgpt_write_code_pic_4.png" alt="ChatGPT Results"/>

    Despite all the problems that arose along the way, it is important to remember how we used ChatGPT to write code. Before the last code regeneration we didn’t pay almost any attention to how the code worked and trusted blindly to everything the neural network generated. We put all the smart work on GPT-4 and only checked the resulting code ourselves. For such an irresponsible approach, when all the work was done without much concentration, the result was pretty good.<br/>
	However, despite the small amount of intellectual and mental effort spent, it is important to keep in mind the amount of time spent to get the solution. We spent a lot of it when we tried to get a working version of a product again. At that point, we think that we should have specified the requirements, reset the context for ChatGPT and started again. It would have saved us a lot of time.

    <Title className="contentTitle" type="h2" id="chatgpt-tips">Tips on how to write code with ChatGPT</Title>
    After the experiment, we have a few tips on how to write code in ChatGPT:
    * **Write accurate and detailed prompts.** Imagine that you give an assignment to a human developer. You need to provide them with enough information to do the task correctly. Otherwise they will ask a lot of questions or write what you didn’t want. Decide what your program or function would do, what you want to include in your code, what parameters you want to send, and more.<br/>
        A little later we used a recommendation from other developers that helps to create a detailed product description to use for initial prompt. This provides a better initial result with required functionality and eliminates regenerations that cause problems. We asked GPT-4 this thing:<br/>
        *I need to develop step-by-step detailed technical specifications for a [product]. Please ask as many questions about the product we would like to build to describe it as precisely as possible. Step-by-step ask questions about each screen, each element.*
    * **Use ChatGPT for finding information about resources and libraries.** A big part of modern programming is finding and choosing the right libraries. And if it's also free, that's even better. As you know, programming is not only about writing code, it's also about understanding how to interact with different systems and how to integrate the necessary components. ChatGPT helps with this analysis and provides you with a list of options for your project to go with.
    * **Ask ChatGPT for code examples.** ChatGPT writes code well for some small functions and tasks. However, it won't work out well on a big product even though the generator will be able to create a solution for a necessary or similar problem, which you can adapt and add in your code.

    <Title className="contentSubtitle" type="h2" id="chatgpt-conclusion">Conclusion</Title>
    Based on the results of our experiment, we can finally answer the questions we asked at the beginning:
    * **Can ChatGPT replace developers?** No, it can’t. At least, not yet. Neural networks can’t provide a complete solution for your project goals, even after a long dialogue with a chat bot. What’s more, the AI doesn’t write quality code for complicated tasks, and the number of errors will increase as the project grows. But now developers must know how to write code with ChatGPT to successfully delegate small tasks to the AI. 
    * **Can ChatGPT write code?** Yes, it can, but with a small nuance: it can write small but efficient pieces of code, not a complex solution. The creation of the basic structure and the implementation of small tasks can be delegated to AI and it will do that effectively.
    * **How is ChatGPT useful in software development?** This tool is useful in many ways:
        * It is useful in studying programming because ChatGPT writes code and shows background information on topics and questions. Thereby, AI makes life easier for entry-level programmers.
        * It can help to start the project from scratch, especially if you don’t know how to do it.
        * Developers get rid of a lot of routine tasks. As mentioned above, ChatGPT handles some small tasks quite effectively. The developer has to deal with more complicated tasks that ChatGPT can’t do.
        * It removes the necessity of constant googling and checking the documentation for libraries, which becomes an important benefit on more complex projects.
        Our team is following trends and has already implemented ChatGPT into the work. Using AI in software development requires technical expertise, so if you need help with your project or you don’t know how to use ChatGPT to write code, feel free to <a class="link-dark" href="#contact">contact us</a>. We will offer you a development team to meet your requirements or we will answer your questions.

      <AuthorInfo image="/images/authors/1.jpg"
                  link="/authors/alexander-gurov"
                  about="Alexander has been a part of the team since 2013 and is deeply interested in building top-notch web development products."
                  socialLinks={[
                      { link: "https://www.linkedin.com/in/a-gurov/", icon: "linkedInIcon" }
                  ]}
      />
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ChatGPT has been one of the most talked-about subjects this year, but can it truly perform the tasks of developers? In this article, we delve into an experiment to determine if ChatGPT can write code and whether it might replace developers in the foreseeable future.

Can ChatGPT Write Code? Let's Experiment to See If It Can Replace Developers Completely

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  <ContentWrapper title="The “Old” Drupal: When It Becomes a Problem, and What to Do About It">
    Drupal is a piece of content management software used to create web apps for media, the public sector, EdTech, healthcare, e-commerce and other sectors. It is generally chosen for its scalability (it adapts well to high load), flexibility (numerous out-of-the-box solutions are available for various business tasks) and its user-friendly content management system. Over its almost 20-year history, a strong community has sprung up around this open-source framework, and 3 June 2020 saw the release of the ninth major version of this CMF (content management framework).
    
    <Title className="contentTitle" type="h2" id="difference">The new version and the old versions: what’s the difference, and what do they offer?</Title>

    Over time, approaches to development and the IT ecosystem as a whole change a lot, and major versions of software reflect this. For instance, the previous big release, Drupal 8, which appeared in 2016, differed from earlier versions in having an object-oriented back end using Symfony components. Implementing the standards and technical capabilities provided by Symfony-based development enabled Drupal’s creators to concentrate on perfecting Drupal-specific features. This made Drupal 8 more attractive for developers and more effective for tackling business challenges.

    New Drupal releases are shaped both by global trends in web development and by changes in the components which Drupal is based on. Older versions of Drupal had fewer dependencies and links to other software, so the framework used to be developed more sporadically: a new major version would come out once every few years, and it would not be backward-compatible with the previous version. This meant developers of Drupal modules would have to almost completely rewrite their code for the new core version. To make use of the new version’s functionality, users would have to independently migrate their sites to the new version. Nowadays, to make Drupal and Symfony work better together, Drupal has adopted a six-month update cycle, gradually introducing new features and marking certain elements as legacy elements.

    <Title className="contentTitle" type="h2" id="old-versions" >Old versions’ end-of-life</Title>

    The main catalyst for the release of Drupal 9 was that support for Symfony 3, which Drupal 8 depends on, is due to come to an end in 2021. When support for an older version of a piece of software is discontinued, official updates, bug fixes and security updates are no longer released, which, over time, makes the system less reliable. For most businesses, it is old versions' end-of-life that is the most important reason for migrating to a new one. Self-supporting security and functionality of legacy software entails risks and increased costs.

    Previously, Drupal's 7 end-of-life was also scheduled for November 2021. Despite the fact that more than half of Drupal projects are made on this version, its support runs counter to the development plans of the framework. But on June 24, 2020, the deadline was shifted. Given the impact of COVID-19 on budgets and businesses, the Drupal community decided to extend Drupal 7 support until November 28, 2022. Migrating from Drupal 7 is significantly more expensive than migrating from version 8 to version 9. An additional year will allow numerous Drupal 7 users to prepare more thoroughly for the last big migration.

    <Title className="contentTitle" type="h2" id="migration">The last big migration</Title>

    Thanks to the way updates are currently handled, the transition from Drupal 8 to Drupal 9 should be smooth and straightforward, as should all other updates planned for the foreseeable future. It became possible thanks to the architectural similarity between the systems. However, moving an old site using Drupal 7 over to the new core will necessitate major reworking of the site’s architecture and data model. Essentially, this means creating a new site, although this should be less work than re-platforming or creating a site from scratch. Migrating site layouts and any custom functionality written for Drupal 6 or Drupal 7 could take as much as 80% of the time it initially took to create them.

    Despite the existence of tools which should make this process easier than when Drupal 8 had only just appeared, migration remains time-consuming and costly. Some companies aren’t prepared to make this kind of investment and use legacy software for years, maintaining the system themselves or outsourcing developers. For instance, although support for Drupal 6 ended four years ago, data from 2020 on the usage of Drupal cores suggests that around 3% of projects are still using Drupal 6 or older versions. This approach is fair enough, but it creates a number of bottlenecks.

    <Title className="contentTitle" type="h2" id="problems">What problems might users of legacy versions run into?</Title>

    <Title className="contentSubtitle" type="h3" id="security-issues">1. Security issues</Title>

    Security issues and vulnerabilities occasionally come to light in both old and new software. The difference is in who has to deal with them. Responsibility for the security of the current version of Drupal is assumed by its developers: they identify potential vulnerabilities and release free security updates. For end users, installing updates is a routine task, whereas independently monitoring and fixing security problems in a legacy system requires attention and manual labour. It’s also important to remember that Drupal exists within a whole ecosystem (PHP, its extensions, Drupal modules and third-party libraries). Having lots of old, unsupported elements in a system always increases the risk of losing data—and your users’ trust.


    <Title className="contentSubtitle" type="h3" id="technical-issues">2. Technical issues and limitations</Title>

    If you’re not bothered by potential security threats, technical limitations can make your life difficult right here and now. First, because the third-party services you need don’t “get along” with your software, you’ll have to write integrations yourself and configure them to take account of older systems’ platform particularities. Second, you’ll have to hand-configure functionality that’s often available in modules in later versions. Third, even if the module you need exists, it’s not going to get updated, so you’ll have to put in the work to keep it stable yourself: third-party services’ APIs occasionally change. Billing, inventory accounting, any CRM, ERP, logistics management, etc.—the more complex your product is, the more elements you’ll have to continuously monitor.

    <Title className="contentSubtitle" type="h3" id="loss">3. Loss of system flexibility and scalability</Title>

    Supporting legacy software means a lot of custom code, and the flexibility and scalability of your system is going to take a hit from that kind of approach to development. One of the main advantages of Drupal is the abundance of different modules, which make experimenting with your product quicker and cheaper. However, there are not enough modules compatible with older versions to cover all of your current business needs. When the market changes fast and your users (clients, marketing experts, editors) need new things from your system, you won’t be able to make these changes as fast as those of your competitors who are using out-of-the-box solutions.

    <Title className="contentSubtitle" type="h3" id="issues">4. Issues with business development.</Title>

    If you want to receive state investment or subsidies, your products have to fulfil certain requirements, including technical ones. Drupal 6 and earlier versions don’t meet these requirements, as they don’t tick the boxes for service security. The cost of support and limited potential for making the changes we described above will also make your product unattractive to investors.

    <Title className="contentSubtitle" type="h3" id="high-cost">5. High cost of support.</Title>

    The code underlying Drupal 6 and Drupal 7 doesn’t conform to modern standards, so there are far fewer developers out there who can do a good job of supporting your product’s performance and security than there are for newer software. What’s more, these are mostly experienced developers with a high hourly rate—and you might end up needing a lot of hours. You might also run into problems with finding support documentation for older versions and with their compatibility with the modern ecosystem. Custom code is always more unreliable, more costly, and more labour-intensive.

    <Title className="contentSubtitle" type="h3" id="need-to-migrate" >How do I know if I need to migrate my product?</Title>

    Despite the risks this article has outlined, we’re not saying that everyone definitely has to make the move right away. You can only make a rational assessment of how urgent it is for you to transition to Drupal 9 by taking into account the specifics of your site and your future plans for it. The November 2021 and November 2022 deadlines gives you plenty of time to evaluate whether you need to make the move, work out how much it will cost, and start working on it in a careful, orderly way. Here are a few things you should take into account to make a comprehensive assessment:

    **Are you expecting to make changes to the design, add new functionality, engage in marketing activities, or see an increase in user numbers? If so, compare the capabilities of the new system and your current system, and the cost of development in both cases.**

    * Could a more advanced system help you to cut down on manual labour? For example, Drupal 9 includes Layout Builder, which lets content managers create page designs without relying on programmers. It’s looking like Drupal is increasingly moving towards making things as simple as possible to use and automating everything, even updates. Maybe you’d recoup the costs of moving to the new Drupal sooner than you think?
    * Is the speed with which you can make changes important to you? What advantages might the ability to make quick changes have for you in the future?
    * What might the consequences be of your system getting hacked? How likely is this? Are you abiding by all the laws around handling personal data?
    * What’s the quality of your code like now? The cost of migration, and the cost of not migrating, are largely dependent on the current state of your site.

    Don’t forget that using old technologies is a sort of technological debt which grows over time and is highly likely to create problems when you try to support and develop your product down the line. Changing standards are not a problem; they’re part of the technological evolution which makes creating reliable, high-performance web products easier.

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Alexander Gurov, Business Development Officer 

Updating technologies on the website is vital for its stable performance. In this article we explain how to identify that it is high time updating Drupal on your website and what it can cause if the issue remains unresolved.

The “Old” Drupal: When It Becomes a Problem, and What to Do About It

<Wrapper emptyHeading backgroundColor="gray">
  <ContentWrapper title="Cloud Team VS Freelancers: Who's Better to Work With?">
    Nowadays, your promising team is no longer confined to your local developers or random individual freelancers. The important question is, how to hire the best developers with a guarantee of services' quality? I’d like to show you what we personally do to achieve it and what advantages we have as a result. 
    Let me begin with a small introduction to our team. We’re a “cloud team”. When you need some web project to get done and you’d like to be sure that it will be done properly and by the most effective way, you definitely should try our “cloud team” in work, actually we’re consists of developers who could become freelancers but they chose to be a part of our team by some reasons I’d like to clarify here. Such developers’ collaboration is very efficient and it works very well for 8 years pleasing our developers as well as our customers.

    I'd like to say that I know very smart, talented, motivated and experienced individual freelancers, and I don't like to offend anyone, but I think there are some obvious cons that you may experience when you hire an independent freelancer and you should take these cons into consideration when you do that. We think that you have to ask yourself some questions that I mention here before hiring a freelancer.

    <Title className="contentTitle" type="h2" id="sickness">1. Sickness</Title>

    A freelancer can get sick, it just happens and usually, it happens unexpectedly. What if a hired freelancer gets sick or even suddenly disappears? Remote agency usually have some developers in reserve, who are always ready to replace a sick developer for some time, so you won’t even notice. The human factor of imperfection won’t affect your business by any means!

    <Title className="contentTitle" type="h2" id="vacation">2. Vacation</Title>

    A freelancer can have a vacation and he definitely should get a vacation once or twice per year at least, but most of the projects have deadlines, and usually, deadlines aren’t going to take freelancer’s vacation without consequences. You don't have to think about it, we'll take care that our developer will get a vacation and we’ll provide you with a smooth temporary replacement.
    What if an independent freelancer would go on vacation? How would you replace him for 2-4 weeks?

    <Title className="contentTitle" type="h2" id="education">3. Education</Title>

    **We have a road map that each developer should pass with a certain period of time, each step out of 5 mostly looks like an exam, most of the time it takes about 3 months of preparations and 5-8 hours of examination in the appointed day. It includes but not limited to:**

    * Web: HTML, CSS, JS, PHP, Databases + different languages and frameworks (depends on the developer’s specialization);
    * Theory: Operating systems, Web technologies, Algorithms, and Data Structures, OOP;
    * Tools and side hard skills: Task tracking tools, Deployment tools, Cloud computing services, Development environment, Debugging tools, Virtualization(Vagrant/Docker), Command Line Interface, Dependency management, Best practices of making project's documentation and project's estimation;
    * Soft skills: Communication, time management, development's methodology, licenses, and NDAs;

    So we encourage developers for growth very much and we have a lot of successful examples of developers transformation from Junior to Senior for 3-5 years. Is there any guarantee that a freelancer will grow day by day? Even experience is not always equal to real growth.
    I understand that your main intention is to successfully implement your project, not freelancer’s education, but if a developer doesn't deepen and broaden his knowledge, there is a high chance that he tries to solve your business problems by not the most efficient way. Some freelancers neglect theoretical basis knowledge and they not always intend to be involved in any form of education because often when you learn you don't earn money and this state of things is not an option for each freelancer.

    <Title className="contentTitle" type="h2" id="technology">4. Technology stack</Title>

    This point is a direct consequence of the previous one. When you come to a freelancer his main intention could be to choose a technology stack that he has already known even if it’s not the most efficient way to develop your project. He could have no motivation to learn new technologies since it takes a lot of time, so he may try to convince you to use the one that he’s already experienced with.
    Our “cloud team” has experts of various technology’s stacks and all together we always try to choose the most efficient option during the initial stage of the project’s assessment, we always can make an assessment for different technologies stacks describing their pros and cons with all specificity regarding to your project to show you the big picture from different sides.

    <Title className="contentTitle" type="h2" id="support">5. Support</Title>

    Each of our developers has a mentor who has a Master's Degree or Ph.D. in Computer Science and more than 10 years of commercial experience. Even the most experienced freelancer can make a mistake and an extra pair of eyes into the code, simple advice or complete code review are essential despite the years of experience.
    Most freelancer work at home all alone without encouraging advice from his colleagues as well as without an opportunity to discuss his technical decisions with more experienced developers, so it can affect their quality of code and motivation. We insist that our developers should work from our office hand by hand with other developers. It motivates them much more, they have a chance to solve difficult problems quite fast if they get stuck, they can discuss a problem with teammates to find the best solution and it allows us to put our finger on the pulse.

    <Title className="contentTitle" type="h2" id="team">6. Team</Title>

    We have 30 developers in our “cloud team”. You can find back-end, front-end, full-stack developers amongst them, but besides we have QA specialists, web designers, and UI/UX designers. We’re a team, a large and powerful unit! If your project would be expanded and you need an extra pair of “coding hands” or you need some design/QA stuff to do, we can guarantee that we would help you with it. A new assigned developer will be the one who is working in the same room with developers who is already working on your project, they already know each other very well and it makes the introduction process of new developers for your project significantly smoother.
    If you need more than 1 developer or you have some work to do for a designer, you have to gather them all one by one in the hope of they will find common ground without pointing fingers at each other if something goes wrong.

    Even if a freelancer has a lot of positive feedbacks you can not say for sure that your project will be the one where he won't get sick, go to vacation, lose motivation or just disappear. 75% of our projects are from clients who have come to us after they had a huge disappointment after working with independent freelancers. Usually their main argument to hire a freelancer was the lower price, but they often lose a lot of time and money, usually, their only option is to rebuild everything from scratch or to make so significant code’s refactoring that would be equal to development from scratch.

    <Title className="contentTitle" type="h2" id="checklist">Checklist: “Before you’re going to find an independent freelancer”:</Title>

    **Here are some points:**

    * What if a hired freelancer gets sick or even suddenly disappear?
    * What if a freelancer would go on a vacation? How would you replace him?
    * Is there any guarantee that a freelancer expands his knowledge day by day to make your web or mobile app works better and better as a result?
    * Are you sure that the technology stack an independent freelancer has chosen for your project is the most appropriate one?
    * Are you sure that a freelancer wouldn’t spend an extra 10 hours because he’s stuck and there’s no one to help him?
    * What if one day you need more developers or design’s/QA work for your project?

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              link="/authors/alexander-gurov"
              about="Alexander has been a part of the team since 2013 and is deeply interested in building top-notch web development products."
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                  { link: "https://www.linkedin.com/in/a-gurov/", icon: "linkedInIcon" }
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  />
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Choosing the right figure for your project can be tricky as there are so many options our there to choose from. In this article we explain the difference when hiring cloud team or freelancers with all the key advantages and disadvantages for each option. See our artiicle to have a full understanding on which option to go with.

Cloud Team VS Freelancers: Who's Better to Work With?

<Wrapper emptyHeading backgroundColor="gray">
  <ContentWrapper title="High Load on Websites: Why Is It of Importance Not Only for Programmers?">
    Whether you’ve pulled off a great ad campaign or published a super-topical article which made the first few pages of search engine results, one of the measures of your success is an increase in relevant traffic to your website. The notion of increasing traffic to their site makes product managers and service marketers happy: their thoughts immediately turn to increased revenues from advertising, growth in sales (if this is an online store or media with a paywall), and more social mentions and repeat visitors. Could there be any downsides? Well, yes, there could, if your service isn’t ready for the increased load. 

    Every user who navigates to your resource and clicks on something, or even just opens a page, creates a load on computing power. If this load on the server increases, and you haven’t made provisions for flexible scaling of your server capacity as part of your project, your equipment ends up pushed to its limits. The result is that your applications’ performance suffers: in layman’s terms, your website or app is slow. You can’t define “high load” with a single number: this is a problem that could affect both a little WordPress blog and a giant like Facebook. The critical number of users will be different for different projects. 

    <Title className="contentTitle" type="h2" id="signs">What are the Signs of Excessive Load?</Title>

    To make the phrase “high load” less abstract, let’s take a look at the issue through the eyes of a user: pages load slowly, you get 502 and 504 errors and database errors, pages don’t open, submissions don’t get saved. Someone looking at the site analytics at that moment would see the page views per visitor falling, the bounce rate increasing, and the site’s search engine ranking decreasing. 
    A more specialised metric which engineers might notice increasing when a site is slow is TTFB, or time to first byte. This is the time that elapses from the moment a browser starts to send a page’s request to the moment it receives the first byte of information back from the server. Poor TTFB is a pretty sure sign of performance issues.


    <Title className="contentTitle" type="h2" id="problems">What Can be Done to Avoid Problems?</Title>

    We’re talking about the kind of load generated by service users, and most of this is predictable. Given the consequences and losses that could result from the website not working as it should, the team responsible for user interaction should always assess whether any actions they’re about to take will generate a spike in traffic. If you’re preparing an ad or SMM campaign, having a sale, or sending out a newsletter which will attract a lot of traffic to the site, tell your engineers what your plans are. Together, you’ll be able to assess whether the increased load you’re expecting will be critical for your system. 

    There are a few ways you can increase the load your site can cope with. You can scale up your system by increasing its computing power, i.e. buying new servers or upgrading your web hosting plan. Another approach would be to speed up your system by adjusting its cache settings and optimising the code it runs (you can read about the many and varied things caching can do here). The solutions you employ can vary depending on the volume of traffic you’re expecting, the type of load (one-off or gradually increasing), and your site’s most frequently-used functions. Increasing your site’s resilience isn’t just a problem for engineers: there are also economic considerations. As your project grows, the cost of scaling increases. To reduce this cost, you should hire experienced engineers and carry out a thorough analysis of your system. 

    Adapting your system to increasing loads is a natural stage in a digital project’s evolution. This article hasn’t touched on the kind of increased load that can occur for reasons that wouldn’t be on a non-techie’s radar: security issues, web crawlers, suboptimal database setup, etc. If the engineers attached to your project are doing their job, these kinds of issues will be resolved without affecting other people involved in the workflow. At the same time, though, to avoid the problems this article has discussed, businesses should forecast their growth so the necessary tech can be put in place in good time.

  <AuthorInfo image="/images/authors/1.jpg"
              link="/authors/alexander-gurov"
              about="Alexander has been a part of the team since 2013 and is deeply interested in building top-notch web development products."
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                  { link: "https://www.linkedin.com/in/a-gurov/", icon: "linkedInIcon" }
              ]}
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Having more traffic on the website than usual can both benefit or affect your digital presence as it all comes down to optimising the website so it would work well even when there is a huge wave of traffic. In this article we explain why it is important to pay attention to it and shed a light on ways to optimise your product for it.