Two Questions for Four Data Visualization Types, and Why It Matters

QuoteNot long ago, the ability to create smart data visualizations, or dataviz, was a nice-to-have skill. For the most part, it benefited design- and data-minded managers who made a deliberate decision to invest in acquiring it. That’s changed. Now visual communication is a must-have skill for all managers, because more and more often, it’s the only way to make sense of the work they do.

A June 2016 Harvard Business Review article by Scott Berinato discusses the four types of data visualization, in their traditional “boil complex stuff down to a 2×2 matrix” method no less.  In short, what works depends on the level of details necessary to convey the purpose.

Two axes of data visualization – what works best depends on the purpose

The overall concepts are reminiscent of concepts by Edward Tufte and his many, excellent, books on visualization.

The HBR article is worth a read for anyone interested in business intelligence, data analytics, or data visualization (which, as Berinato says, is probably a misnomer – it’s not the visualization that matters, but the question it seeks to answer).

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Howard Chen
Vice Chair for Artificial Intelligence at Cleveland Clinic Diagnostics Institute
Howard is passionate about making diagnostic tests more accurate, expedient, and affordable through disciplined implementation of advanced technology. He previously served as Chief Informatics Officer for Imaging, where he led teams deploying and unifying radiology applications and AI in a multi-state, multi-hospital environment. Blog opinions are his own and in no way reflect those of the employer.

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