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dbt Meetups are networking events open to all folks working with data! Talks predominantly focus on community members' experience with dbt, however, you'll catch presentations on broader topics such as analytics engineering, data stacks, data ops, modeling, testing, and team structures.
Join hosts Brooklyn Data Co and speakers from DonorsChoose and WeWork.
For the best Meetup experience, make sure to join the #local-nyc channel in dbt Slack (https://slack.getdbt.com/).
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✨ Speaker Lineup✨
🗣 Mohammad Radiyat, Data Scientist at DonorsChoose
Making Equity Transparent: Using dbt to Secure our Demographic Data
DonorsChoose is a national nonprofit that makes it easy for anyone to help a teacher in need, moving us closer to a nation where students in every community have the tools and experiences they need for a great education. Mohammad will cover how the data team at DonorsChoose allowed thier colleagues to access aggregated equity data while securing their teacher demographic data using dbt. Some highlights of the talk will include using macros to keep transformations DRY, the awesomeness of incremental models, and the ease of dbt Cloud in managing their dbt jobs.
🗣 Raify Hidalgo, Data Engineer & Max Kang Senior, Data Engineer
Building a Unified Streaming and Batch Pipeline with DBT and Snowflake
Raify and Max will dive into the implementation of a batch and streaming pipeline they developed at WeWork, which leverages dbt and Snowflake. They aimed to use their existing stack in order to optimize for speed to delivery, along with minimal debugging time, and minimal learning curves. This was their first foray into the world of streaming data modeling, where they owned most of the end-to-end pipeline. You'll hear all about the considerations they made, what they learned, challenges they faced, and why - in the end - they wouldn't have been able to get up and running without developing on their existing stack: Airflow, dbt & Snowflake!
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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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