The Best Data Visualization Tools for 2019
Where business intelligence (BI) tools can take huge swaths of data and parse that into digestible data points, data visualization is the presentation portion of that equation. Think of it as the pie chart function of your favorite spreadsheet, only much more powerful. The purpose of such imagery is to quickly transfer information from the machine to the human brain, not only efficiently but also in the most meaningful manner possible. Therefore, it is not the aesthetic value of a visualization that counts but the clarity of the message it conveys.
However, the conciseness necessary for clarity does not preclude complexity in the message. Since much of the information humans must consume is complex and nuanced, data visualizations are configured alone and in groups to tell a larger story through images. An example of a single configuration is any visualization that reveals more granular or related information when the viewer clicks on or performs a mouseover on a section of the illustration. Examples of group visualizations include just about every BI app dashboard ever made.
Indeed, data visualization is such an integral part of self-service BI tools that the tools to make and publish them largely share common feature sets. As expected, in our recent review roundup of the best self-service BI products, we found the vast majority to be capable of data visualization operations.
However, customers looking to really exploit data visualization should look at these tools carefully and exclusively through that lens before making a buying decision. After all, sometimes the right tool to parse your data may not offer a sufficient visualization palette for your needs. For example, you may want the ability to build a custom infographic or create interactive visualizations, but not all BI apps provide those options. You may need to invest in a combination of tools to get both the analytics and the visualization tools you need.
In short, data visualization is a visual depiction of information. It is imagery dedicated exclusively to messaging or presenting information. Data visualization tools can automatically create visualizations, enable you to create your own, or offer both capabilities.
At the lower end are simpler and evenfree data visualization tools dedicated to building infographics rather than performing sophisticated data analytics. Some of these tools include Tableau Gallery and even Microsoft Power BI.In January 2018, Tableau introduced a new data engine called Hyper that the company claims gives users up to five times faster querying speed over previous versions. Meanwhile, in July 2018, Microsoft rolled out new features for Microsoft Power BI, such as integration of Big Data directly into the Power BI web service.
At the higher end are tools that can change visualizations on the fly, in the same way that outputs from sophisticated algorithms change after repeated direct querying of real-time data (i.e., streaming data) and across multiple data sources. The tools occupying the middle of the spectrum do not represent real-time data but still produce visualizations from advanced analytics outputs.
The self-service BI apps we reviewed contain average to higher-end visualization tools. Some of the tools contain strong natural language query capabilities like Sisense, and others bring real-time analytics for the Internet of Things (IoT), like SAP Analytics Cloud.In short, you cannot judge the quality of the underlying analytics engine by the cover of its art package. Some very powerful analytics come with pitiful to passing visualization capabilities. Conversely, some pitiful to passing analytics come with some pretty impressive visualization features.
Since we originally reviewed these BI tools, IBM has discontinued offering IBM Watson Analytics for purchase. Instead, IBM introduced Cognos Analytics 11.
