Low Code Development

Low-Code Development Tools are the Future of Data Analytics

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Data analytics is an evolving science. New technologies, tools, and trends in the space are being developed and discovered all the time. Low-code/no-code BI solutions are bringing a lot of changes to the future of both data analytics and modern app development. These tools and technologies are becoming invaluable for their ability to help organizations build BI apps faster than ever before, as well as to allow easier access and use of data for non-technical users.

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The Need of Low-Code Development Tools in Data Analytics

In today’s data-driven world, data analytics capabilities and tools are fundamental for any organization’s success. In the past, data analytics was only possible with coding and using coding languages for data science such as Python and R. Nowadays, however, with the advancement of technologies and the rise of low-code development platforms, analyzing data (both structured and unstructured data) has become a more streamlined and efficient process that can furthermore help speed up data analytics experimentations and deployment.

Low-code BI tools provide a visual drag-and-drop interface that makes it easier for non-technical users to get started working with data even if they haven’t done it before. Many platforms also provide pre-built templates and models so that users can save time from building those from scratch. Flexibility is also a great advantage. Low-code analytics tools provide a free-form approach to data construction, meaning that users can collect and merge data from multiple different data sources into one view.

Of course, low-code development platforms on their own can help those who don’t have an integrated analytics solution to build one for themselves much faster compared to if your developers have to write code from start to finish. By using such development tools, you can have a fully functioning analytics solution with powerful reporting and data visualization capabilities in hours or so rather than months of traditional hand coding.

And it goes without saying that low-code tools can help you see results faster. On one side, the data analytics process is much quicker, so the time-to-insights is almost instant. On the other side, if you use such tools to build apps on your own, you can hit the market or start upselling those apps to your customers, and as a result, increase your revenue sooner.

Low-Code BI as the Future of Data Analytics

Gartner predicts that by 2024, low-code adoption will be so widespread that 75% of the software solutions built around the globe will be made with the help of such tools. Also, another survey by Reveal shows that citizen developers and low-code/no-code tools can help meet the demand for building applications faster and with fewer resources. More than half of the survey’s respondents (54%) said that they are planning to economize in 2022 by using low-code/no-code (app builder) tools to automate many developer/IT/analyst processes, all while reducing the need to hire new employees.

With these facts in mind, it is evident that low-code is bringing the power of data analytics to the masses and that every organization needs to invest in such tools to remain competitive on the market, increase productivity, and save on resources.

Here are a few, summarized reasons why low-code tools are the future of data analytics:

  • Low-code tools and platforms are much easier to use than traditional hand coding
  • Low-code tools and platforms allow users to create apps without any technical knowledge
  • Low-code tools and platforms enable automation
  • Low-code tools and platforms provide no-code ML to beginners
  • Low-code tools and platforms ease the data collection process
  • Low-code tools and platforms help cleanse and prepare data
  • Low-code tools and platforms accelerate time to insights
  • Low-code tools and platforms can save your organization money all while generating higher revenue

Organizations of all industries and sizes can use low-code analytics for various tasks, including forecasting, customer segmentation, and fraud detection, to name a few. For example, with the use of a low-code BI tools retailers can quickly build custom dashboards with minimal to no coding to help them streamline in-store operations, gain insights into customer behavior, optimize the customer experience, and improve promotions. Manufacturers can monitor their machines, orders, inventory, and supply chain in real-time in order to identify risks and help predict future risks by spotting trends and patterns throughout the entire manufacturing process.

Low-code tools are particularly well suited for data analytics tasks that require a lot of data preparation and are great for more complex analysis that requires custom coding.


The future of data analytics is low-code mainly for the reason that it helps democratize data analytics so that everyone regardless of knowledge and skills can easily access the tools and techniques needed to make data-driven business decisions. But, of course, low-code platforms are not perfect. Depending on the platform, you can face some limitations to what you can create, or how easily you can use them. So, if you’re considering investing in a low-code platform, it’s important to do your research and understand the pros and cons of different vendors and solutions before making an investment decision.

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