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Building an Analytics Production Line with Lee Feinberg, CEO at DecisionViz

Richie and Lee explore the limitations of traditional dashboards, the importance of a product mindset in data viz, the role of comms and standardization in analytics, the intersection of AI with dashboarding, and much more.
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Lee Feinberg

Guest

Lee Feinberg

Lee runs DecisionViz, providing training and consulting to organizations to improve their people, process, and culture around visualization and storytelling. He's a course creator for the University of Chicago, an instructor for TDWI, and an Adjunct Faculty Instructor for NYU School of Professional Studies. Lee is also a Tableau Certified Associate Consultant, 4 times Tableau Ambassador, and a long-term Tableau Partner. Previously, he was a Research Advisor for the International Institute of Analytics, the Founder of the 501c data community, and a senior manager at Nokia.

Richie Cotton

Host

Richie Cotton

Richie helps individuals and organizations get better at using data and AI. He's been a data scientist since before it was called data science, and has written two books and created many DataCamp courses on the subject. He is a host of the DataFramed podcast, and runs DataCamp's webinar program.

Chat with AI Richie about every episode of DataFramed - all data champs welcome!

Key Quotes

The data isn't really important. It's what are people going to do with it? What outcomes are they looking for? Even what decisions and actions are they trying to take? That's really what's important.

The whole premise of it is really about communication. That's really what all of this is about, right? It's not about data, it's not about visuals or the specifics. The goal is to communicate an idea as easily as possible.

Key Takeaways

  1. Rethink dashboards as products rather than just data visualization tools, focusing on the outcomes and decisions they are meant to drive

  2. Implement a product mindset in dashboard creation by establishing foundational principles, understanding user needs, and engaging users to ensure the dashboard meets its intended purpose.

  3. Standardize language and visual communication within your organization to avoid confusion and improve data literacy, ensuring everyone is on the same page when discussing business metrics.

스크립트

Richie Cotton: Hi, Lee. Welcome to the show.

Lee Feinberg: It's good to see you.

Glad to be here.

Richie Cotton: Great to see you again. So, of all the dashboarding experts I know, you're perhaps the most negative about dashboards of all of them. So tell me what's wrong with dashboards?

Lee Feinberg: So just jump right into it. Huh?

Richie Cotton: Absolutely. We're diving straight in there.

Lee Feinberg: It's not that something is wrong with dashboards. I wouldn't really frame it that way. I think it's how people think about them and how they've thought about them for probably 30 years. really what I'm trying to do with my clients is change that perspective. So when you think about a dashboard, it immediately, go into this idea of, Oh, I've got to get my data and make some charts and put it all together.

And. That's what my dashboard become and especially these days when businesses are moving even faster and trying to make heads or tails of even more data than they've had before the data in some ways actually gets in the way, The data isn't really important. It's what are people going to do with it?

what outcomes are they looking for? Even what decisions and actions are they trying to take? That's really what's important. And so when I talk about dashboards and why I don't like them, it's because people think about them in the nature of just having to display data. And that's not really what they should be used for.

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