In Analytics, Visualization

A recent ComputerWorld article, Why Analytics Is Eating The World, contained the comment, “The best analytical insights come from user-generated dashboards running on top of IT-managed infrastructure.” While there is clearly a need for business users to create their own charts using visualization tools like Tableau, the idea – which is challenged in the article itself – that these dashboards can produce the “best analytical insights” is questionable. Vendors and a professor are quoted in the article that users need to be trained in using these tools and in data science techniques to correctly analyze the data.

There are a number of things in the article that don’t add up:

  • First, the main benefit of end user data visualization tools is that users don’t need much training, so to recommend that users be trained to correctly use the visualized data runs completely counter to that benefit.
  • Second, the idea that these end user tools do “analytics” has to be taken with a sizable grain of salt. If “analytics” means displaying charts with basic algorithms, then fine. But for most of the industry, serious analytics–especially of diverse and large volumes of data–requires complex algorithms created by people who spend years at school learning how to create them. There’s a huge difference between people doing data analysis of what they see on a screen and software doing data analysis and presenting the results to users.
  • Third, how does the user know whether the data they’re looking at is “correctly” analyzed or not? Regardless of who writes a prediction algorithm, the results are always questionable. That’s not to say there’s no value in analytics, just that it’s critical that the user understands the conditions under which the analysis was performed, the quality of the data used, and the mechanisms used to produce a result. The only way a user can be confident in what they see is by understanding how confident the software is in the analysis it generated.
  • Finally, while it’s useful to have visual dashboards that tell businesses how many products they sold last quarter, companies are realizing that to be competitive they need real-time advanced analytics that provides insight into what’s happening right now and in the future, not yesterday or a month ago. In many cases, the visualization of the data itself is of course, critical, but the real value to a business lies in the analysis.

In the second part of this post, I’ll share some examples of analytics beyond dashboards.

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