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Data Literacy Programs with Megan Brown at Starbucks

Data-Driven Podcast

Listen to Megan Brown talk about building a knowledge management and data literacy program and experience launching “the Wayfinder” that offers Starbucks employees a search engine with links to self-service dashboards supported by a library of training material and documentation to use the data and metrics to make smarter decisions regardless of their role.

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Meet our Guest

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Megan Brown

Director, Data Literacy, Starbucks

Megan is the Director of Data Literacy for the Analytics & Insights team at Starbucks. Megan sets the strategy and roadmap for the team, including establishing A&I policy for launches, monitoring adoption and project transitions to ensure organizational resilience. Megan founded the Data Literacy team at Starbucks to drive analytics product adoption and translate complex concepts for business stakeholders.

Meet our Host

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Dave Mariani

Chief Technology Officer, Founder, AtScale

Dave is the founder of AtScale and is the Chief Strategy Officer. Prior to AtScale, he was VP of Engineering at Klout & at Yahoo! where he built the world’s largest multi-dimensional cube for BI on Hadoop. Mariani is a Big Data visionary & serial entrepreneur.
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One of the spots I moved into was knowledge management and data literacy. I did that because I was the Data Scientist that kept asking, why are we doing it this way?

In its most simple form, data literacy is about using data to do your job. Can you find the data? Can you access the data? Can you get the data? Can you manipulate the data? And can you interpret the data? I’m an idealist and I think everyone at the company should be able to do those things to some extent with their data applicable in their role.

I think a lot of people don’t know what data exists and that’s why knowledge management supports data literacy. There’s also this idea that analytics or data science is kind of magical.

One of the first things my team turned out when we were created as the Knowledge Management & Data Literacy team was what we call “the Wayfinder”.  Like good data and decision scientists, we tried to build it in the most automated way.

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