AI and data analytics are fueling multiple sectors to make them smarter. In this blog, we picked the software development segment to find out how influential these technologies are for its operations.
Today, software development is not just about editing, social media, or internet browsing. We are in the era of automation, driverless vehicles, wireless appliances, humanoid robots, and more.
As such technologies are nothing without the proper software to power and control them, new innovations keep coming into the existence.
Today, we have technologies such as AI and data analytics to support these growing innovations of software development for different purposes. Moving forward, in this blog, we will discuss how AI and data analytics technologies are joining hands to change the software development industry.
But as AI and data analytics are usually considered very similar, let’s have a short introduction to differentiate these terms from each other.
Difference between AI and data analytics
In simple terms, data analytics is limited to the process of observing historical data to find patterns and predict possible outcomes accordingly. Depending on the size of the data and impacting factors, each dataset can have different outcomes.
AI, on the other hand, is much wider. The technology is designed to copy the way the human brain works but to perform many more complex tasks.
It uses data to not only predict the future but to make assumptions independently.
The technology also works beyond mathematical or scientific data.
Outcomes can be numbers or art pieces, depending on the nature of AI.
It clearly shows the role USA plays in the global tech market. With such influences in the background, the decision to look at the top software development companies usa
for technology partners is obvious.
Influence of data analytics and AI on software development
Now, even though both technologies have different definitions, for many processes including software development, AI and data analytics work together. So, without wasting any more time, let’s dive into the discussion of the impacts that these technologies have on the software development industry.
Personalized usage experience
Big data generated by users helps developers in offering a more personalized user experience. Data such as the number of hours users spend on the app, videos they browse, products they browse, etc are used to fuel AI.
It uses machine learning algorithms and data analytics algorithms to automate the process of shortlisting and showcasing the content or products users might love.
Modern software and apps such as Spotify or Netflix are already using these advantages of the technology. Banking apps and fintech apps are also expanding the usage of these techniques to help users in finding suitable investments and financial products for them.
Automated code deployment
For new developers, software development has become a much lesser task than it used to be. However, with the automation of code deployment, the software can be built but with preprepared elements to integrate.
For example, there are low code tools that can help users in building software with minimum requirements of codes.
By using pull to add features, you can just modify features, UI, icons, and more as you want. AI and data analytics can automate the process of defining behaviors and actions for the app as you integrate features.
To build software faster with the least budget and resources possible, low code development is turning out to be the growing trend.
As you can see in the above report by Statista
, low code platforms are growing to cross tentatively $47.31 billion global revenue by 2025. By 2027, the market is expected to grow with a CAGR of 26.1%.
With the increasing speed of businesses going digital to keep up with the competition, low-code platforms might get more popularity than these predictions.
Automated software testing
To deploy perfect software in the market, it has to be foolproof. And as bigger your target market gets, the more variations of devices you have to consider to optimize your software.
Now, as you might have already faced the pain of locating minor errors in the code manually, you can imagine how handy testing tools supported by AI in mobile app development processes can be.
These tools are used to test software with multiple operating systems and models to find out possible glitches that users might face after the launch of the software. The best part of these tools is that they also provide you with the exact source of the glitch so that you do not have to do the hustle of going through each and every line of code.
With the help of data analytics and AI, these tools can save your software from negative feedback.
Improved cyber security
By using the data generated through evolving cyberattacks, AI algorithms and data analytics can help in predicting and blocking possible future cyberattacks on software to steal or corrupt data. Industries such as finance are using these technologies to protect user data and company data from any such threats.
AI also helps in keeping an eye on connected devices that can become the gateway of cyber attacks due to any software or hardware failure.
Accurate estimations
For successful software development companies, it is crucial to be clear about the estimated delivery dates and costs of their products. That is where AI and data analytics techniques can come into play.
By using requirements analysis and predictive analytics methods, these technologies can help developers in identifying tentative deadlines and budgets that can be useful in making clear strategies. To positively influence the client retention ratio, it is a good approach to deliver products by the time it was promised without compromising the quality factor.
Conclusion
In this blog, we covered some real-life examples of the influence that AI and data analytics can have on the software development industry. After going through these points, it is clear that even though these technologies have still unexplored potential, they are already assisting developers in improving their productivity and quality with an extensive percentage.
In the end, we hope that this blog on how AI and data analytics are transforming software development operations was useful. We will return to you with such informative blogs soon.
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