dbt Meetup at Warby Parker

This is a past event

115 people went

Details

This event is hosted by Warby Parker (www.warbyparker.com) and open to all folks working with data—while we'll predominantly focus on people's experience with dbt, we're also very interested in broader topics related to analytics engineering, such as data stacks, data ops, modeling, testing, and team structures.

Doors open at 6pm, for a 6:30 start! We'll bring the food and drinks, just make sure you have your ID to sign in!

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Speaker Lineup
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Sean McIntytre, Lead Data Engineer
👓Warby Parker
Ever wondered how dbt actually works? At Warby Parker, the team had a look under the hood.
In this presentation, learn about the inner workings of dbt, and how anyone can build new functionality in dbt just by writing code in their own dbt project. Warby Parker will also share some of the ways they have extended dbt, and how they contributed that code back to the community, making dbt better for all of us.

Andie DeLeón, Data & Analytics
🏃‍♀️P.volve
You may have heard the term "single view of the customer" before. Before you get there, you need to be able to stitch together all your users from the several different SaaS tools your business is using. Sounds easy right? What about when some sources have user_ids, others have emails, and others only have a tracking cookie? Learn how P.volve built a "unified users" model, where one record represented (their best guess) of an IRL person, by joining together several data sources.

Joe Naso, Technical Product Manager
🧠 pymetrics
You've all heard the talks about how wonderful things are after the implementation of new technology, but they tend to skim over how bumpy the ride there can be. pymetrics rolled out is first data warehouse only to find it moving quickly from an afterthought to the primary data source for a number of client-facing products. Learn about all the pitfalls and mistakes the team made during implementation and roll-out, and hopefully, avoid them when it's your turn.

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dbt is a command line tool that speaks the preferred language of data analysts everywhere—SQL. With dbt, analysts take ownership of the entire analytics engineering workflow, from writing data transformation code to deployment and documentation.
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