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More and more companies are raising the “data-led” banner as manifest operational excellence. But is it true? Who's leading who? In her talk, long-time Coalesce dynamo, Emilie Schario (Amplify Partners) challenges data teams to start treating data like a product not a prophet—no better or worse than the people and processes it represents.

Check the slides here: https://docs.google.com/presentation/d/16Zeffh3ODiRkTj_mnugnMdozC4ex-Q4ejyJl_Y33mJc/edit?usp=sharing

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Today I’m chatting with Emilie Shario, a Data Strategist in Residence at Amplify Partners. Emilie thinks data teams should operate like product teams. But what led her to that conclusion, and how has she put the idea into practice? Emilie answers those questions and more, delving into what kind of pushback and hiccups someone can expect when switching from being data-driven to product-driven and sharing advice for data scientists and analytics leaders.

Highlights / Skip to:

Answering the question “whose job is it” (5:18) Understanding and solving problems instead of just building features people ask for (9:05) Emilie explains what Amplify Partners is and talks about her work experience and how it fuels her perspectives on data teams (11:04) Emilie and I talk about the definition of data product (13:00) Emilie talks about her approach to building and training a data team (14:40) We talk about UX designers and how they fit into Emilie’s data teams (18:40) Emilie talks about the book and blog “Storytelling with Data” (21:00) We discuss the push back you can expect when trying to switch a team from being data driven to being product driven (23:18) What hiccups can people expect when switching to a product driven model (30:36) Emilie’s advice for data scientists and and analyst leaders (35:50) Emilie explains what Locally Optimistic is (37:34)

Quotes from Today’s Episode “Our thesis is…we need to understand the problems we’re solving before we start building solutions, instead of just building the things people are asking for.” — Emilie (2:23)

“I’ve seen this approach of flipping the ask on its head—understanding the problem you’re trying to solve—work and be more successful at helping drive impact instead of just letting your data team fall into this widget builder service trap.” — Emilie (4:43)

“If your answer to any problem to me is, ‘That’s not my job,’ then I don’t want you working for me because that’s not what we’re here for. Your job is whatever the problem in front of you that needs to be solved.” — Emilie (7:14)

“I don’t care if you have all of the data in the world and the most talented machine learning engineers and you’ve got the ability to do the coolest new algorithm fancy thing. If it doesn’t drive business impact, it doesn’t matter.” — Emilie (7:52)

“Data is not just a thing that anyone can do. It’s not just about throwing numbers in a spreadsheet anymore. It’s about driving business impact. But part of how we drive business impact with data is making it accessible. And accessible isn’t just giving people the numbers, it’s also communicating with it effectively, and UX is a huge piece of how we do that.” — Emilie (19:57)

“There are no null choices in design. Someone is deciding what some other human—a customer, a client, an internal stakeholder—is going to use, whether it’s a React app, or a Power BI dashboard, or a spreadsheet dump, or whatever it is, right? There will be an experience that is created, whether it is intentionally created or not.” — Brian (20:28)

“People will think design is just putting in colors that match together, like, or spinning the color wheel and seeing what lands. You know, there’s so much more to it. And it is an expertise; it is a domain that you have to develop.” — Emilie (34:58)

Links Referenced: Blog post by Rifat Majumder storytellingwithdata.com Experiencing Data Episode 28 with Cole Nussbaumer Knaflic locallyoptimistic.com Twitter: @emilieschario

If you're like most data workers, you probably spend a little bit of time reacting to and servicing data requests, a bit more time on some larger analysis projects, and then you've got a big pile of free time where you're wondering what else you should be doing. Oh. No? You're absolutely drowning in work and questioning whether you're actually providing value? Yeah. That's actually much more common. We were just kidding with that opener. The great news, though, is that Emilie Schario joined us to talk about different tactics (strategies?) for finding the capacity to do more and better work, regardless of your level in your organization. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Your company has one definition for revenue across the organization, one definition of the customer, and one definition of sign-up. For people whose jobs are so defined by ensuring we're aligned, we can't seem to standardize on one definition for the Data Scientist. In this talk, Emilie Schario (Data Strategist-in-Residence at Amplify Partners and longtime dbt community member) proposes we lobby against the title Data Scientist, instead choosing some variation of the Core Four Data Roles: Data Analyst, Analytics Engineer, Data Engineer, and Machine Learning Engineer. Register to catch the rest of Coalesce, the Analytics Engineering Conference, at https://coalesce.getdbt.com. The Analytics Engineering Podcast is brought to you by dbt Labs.

Join us for a fireside chat with members of the Netlify data team to get an inside look at how their team gets work done. We'll learn how their data team is structured, some projects they've recently worked on, and what's coming up for the team!

Featured speakers: Emilie Schario, Senior Engineering Manager, Data and Business Intelligence with Netlify Laurie Voss, Senior Data Analyst with Netlify Francisco Lozano, Senior Analytics Engineer with Netlify Brian de la Motte, Senior Data Engineer with Netlify