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aspects of data interaction

Next, check into its exporting capabilities. Once you’ve built your query and visualization in the BI tool, what are your options for exporting it to where other folks can consume it? Key options here should include not just a variety of flat graphic formats (i.e., CVS, JPEG, PDF) but also code snippets that can be dropped directly onto webpages, incorporated into other apps via open application programming interfaces (APIs), and rendered in the best way possible on both desktop and mobile devices.

Finally, if your business is collecting Big Data or is about to enter into such a venture (for example, embarking on an IoT offering), then look at a product’s advanced processing capabilities. Some tools act mainly as querying front ends for back-end data warehouses intended to do most of the processing your queries require. That can be difficult if the data warehouse is under a constant query load already, and it can be downright impossible if your queries will span data sources outside of the data warehouse. In such situations, the BI tool will need to provide the performance muscle to crunch your query’s numbers, which means support for advanced data processing capabilities (such as in-memory processing) can be crucial. Again, when evaluating your tool using its free trial, make sure to test its performance capabilities by running as many complex queries through it as you can.

Data visualization can definitely be considered the pretty face of data analytics. It doesn’t change the numbers or the questions, it simply gives you more ways of looking at them. That can be invaluable for some organizations but completely unnecessary to others. If advanced analytics is what your organization needs, then evaluate self-service BI tools based more on their number-crunching capabilities than on their visualization features. But if you’re trying to bring an easier yet deeper view of all the data your organization is collecting to a wider swath of your employees, then data visualization is of prime importance. Just remember that not all people understand all images easily. People learn and ingest information in different ways. Know your audience and choose visualizations that work best in communicating with that audience.