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Data Visualization in Business Intelligence

by | Feb 8, 2021 | Articles

Data visualization is the process of preparing visuals using data and then presenting them in the right form to a right audience. The key objective is to prepare visualizations in such a way that they are immediately understood by the audience and convey a right meaning.

This is obviously not an easy thing to do. However, modern visualization tools have become powerful and easy-to-use instruments. Meanwhile, data visualization is a growing trend in the analytics industry.

As data became plentiful, it is extremely important to know how to make sense of all that data. You may have the richest data in the world, but if nobody understands and uses it, then it is useless.

Power of visual storytelling

A few weeks ago, we wrote about the importance of telling inspiring stories through data. One of the most effective ways to tell an engaging story is to have powerful visualizations.

Many aspects of public speaking and storytelling in the tech industry have improved significantly over the last decade. However, poor visualization still remains one of the biggest problems of tech speakers, said Boris Hristov, the founder of presentation agency 356labs and a PowerPoint MVP, during an interview with Time to Shine Podcast.

“The biggest differentiator in public speaking in 2021 will be the design of visualizations,” said Hristov, a top-rated international speaker.

The visual part of a presentation is the most important one. It activates the parts of the human brain that are responsible for emotions, memory and decision-making.

Data visualization in business intelligence (BI)

Data visualization is an integral part of BI tools. Naturally, modern BI tools have strong data visualization capabilities. In fact, some BI tools, such as Tableau, were originally data visualization tools. However, in time they became full analytics tools, capable of everything from data preparation, modeling, exploration, and visual presentation.

The ultimate goal of data visualization in BI is to build dashboards and data-based reports. Depending on a need, dashboards can convey a single story to many viewers or, alternatively, contain many stories for a single user. The key advantage of dashboards is that they’re highly customizable, can be easily shared with everyone or, on the contrary, put under permissions and be available only for certain users and departments.

Below are the three advantages of using self-service BI:

  1. They don’t require database expertise to use. This means business users can start using self-service BI tools pretty much right away. Often your company would need IT professionals to set up BI by connecting it to required data sources, make sure compliance and security issues are resolved. Once these things are done, end-users can start using self-service BI tools themselves. Obviously, the understanding of SQL and complex statistics would definitely be helpful. However, these aren’t necessary requirements. Modern self-service BI tools let end users bypass the IT bottlenecks in their daily operations.
  2. BI tools are used as a unified front-end to multiple databases and different data types. BI tools can import data from a variety of sources, both structured and unstructured, and put everything together. After that users can find insights and visualize all this information. This is incredibly powerful in the age of big data, especially when data is found everywhere, not just sitting neatly inside a company’s SQL server.
  3. Modern BI tools can be easily integrated with other software. Gone are the days when you had to import visualizations to flat graphic files and then print handouts. With BI tools one can share a code snippet and embed a report onto a website. That way a dashboard can be directly shared with people who are not even using a BI app. These visualizations can be connected to databases using live connectors, which means the visualizations will change on the fly, as data in a source change.
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