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Why the three different styles matter when it comes to learning from data

James Richardson, Business Analytics Strategist at Qlik | May 19, 2016
Not everyone benefits equally from data visualizations, so such learning needs to be tailored to auditory, visual, or kinaesthetic styles.

Finally, for the visually led learners, the options will grow both in terms of new visual forms and in the output devices visuals are rendered on. This could mean taking advantage of very large, ever-higher resolution displays to enable the rendering of massive data sets and perhaps practical virtual reality experiences that allow analysts to work within and explore immersive data spaces. 

Overall, more support for a range of learning types is critical if BI is to deliver as much value to decision makers as it can from the data-driven possibilities open to them.  A caveat though: delivering information in more forms is only useful if people can make sense of the data -- that is, if they know how to read it, if they are data literate. Perhaps just like with today's "code of conduct" training programs, organizations should be mandating training in data literacy. After all, data literate employees are a driver of competitive advantage. As data literacy becomes more prevalent, we'll see more demands for and of data, which can only result in reaching better, faster decisions with BI when it caters to a full range of learning styles.


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