When I speak with business and IT leaders what they would like to improve with their current BI platform, many of them answer “we want more data visualization.” Well, those leaders are in luck as data visualization platforms that work along-side analytics are popping up all over the market. Filled will bells and whistles ready to present company data using an array of colors, word clouds, and heat maps to wow the audience. And sometimes the audience is so wowed that a key question gets missed: How reliable is the actual data analysis?
In a blog article written by Joanna Schloss called “Why Great Data Visualization (Alone) Does Not Equal Great Insight,” Joanna talks about how great visualization by itself does not transcribe into great insight. She makes this great analogy,
“Data and analytics are like the foundation and structure of a house. Visualization is the exterior aesthetics – be it great trim, a coat of paint or beautiful landscaping. The exterior of a home can look amazing, but without a solid structure, the home will never pass inspection. Similarly, if not grounded in proper analytics, data visualization crumbles once you dig below the surface.”
Schloss believes that the visualization often makes us assume that the analysis is valid and it is the responsibility of the audience to not take the presentation at face value. Don’t assume that that “the underlying analytics are sound, that supporting data is valid, and that the right questions are being asked to begin with.”
Schloss offers up this example, “take the general example of word clouds, a popular form of visualization. Dazzling to the eye, they’re more often than not an empty visualization, largely because their presenters rarely explain the supporting data or analysis, and their consumers are rarely able translate them into an actionable business insight. So the presenter displays the word cloud, the reviewer nods in approval, but neither party has enriched their understanding of the business. Perhaps not the best use of precious corporate resources.”
The key takeaway here is that visualization is secondary to the data analysis underneath it. When presenting visualization have a firm understanding of the supporting analytics. Joanna Schloss makes this analogy, “just like the house, where a glossy coat of paint on the top can cover a massive structural flaw, so too can visualizations that aren’t rooted in sound data analytics mask structural flaws in your business processes.”
Click here to read the entire Dell blog article written by Joanna Schloss.
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