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Home » Dave Wells on data literacy

Dave Wells on data literacy

June 14, 2018 by Ted Cuzzillo

Few people in the data industry today are better qualified to opine on data literacy than Dave Wells.

He’s had a decades-long career with data, including TDWI education director for eight years, now the education director at eLearningCurve, and most recently an industry analyst with Eckerson Group. He and I developed and taught a TDWI course on data storytelling.

He has given data literacy and related issues more thought than almost anyone else I know. I asked him for his thoughts on it.

I think data literacy has been a need starting with the introduction of self-service tools. But it hasn’t had much attention until recently. Instead, we seem to embrace every new technology as if it is magic that will solve problems. Then we’re surprised when it solves some problems and creates new issues.

We are now at the point of recognizing the new problems of self-service, including literacy.  I remember Gerry Weinberg telling me many years ago that we fool ourselves when we think we’re problem solvers. We’re really problem traders. And if we’re good at it, we trade big ones for little ones.

In any case, the new problems brought by self-service are many, including governance challenges and a lot of other stuff. But one that has taken some time to gain attention is the problem of having lots of people doing data preparation, analysis, and visualization without strong data skills.

Data literacy (as with language literacy) includes both reading and writing skills. With data, that means ability to read visualizations as well as ability to create them. (I have a half-day course about this.) It also includes the ability to evaluate the fitness of data for a particular use case, ability to judge data quality, and all of the skills needed to prepare data for analysis.

Over the past year or so I’ve been adding the concept of data coaching into my discussions of self-service and data governance. I think a culture of coaching is a realistic way to increase data literacy throughout an organization. Different individuals will have data knowledge and skill in different areas — visualization, preparation, quality, and data domain expertise. They can coach where they have skills and receive coaching where they need to build skills — sort of a collaborative approach to focusing on collective literacy as well as individual literacy.

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