Using dbt to understand open-source communities

Srini Kadamati
Senior Developer Advocate, Preset

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About this talk

Open-source projects, and the communities that develop around them, are the lifeblood of modern technology. Some companies, like dbt Labs, create open-source products and cultivate a community around them. Others, like Preset, build commercial projects on top of pre-existing open-source ecosystems. But how do you understand your community and the types of things that could help make it successful?

In this talk, I'll showcase the portable, fully open-source data stack that ingests, transforms, and analyzes data from the channels that your community lives in (Slack, Github, etc). The stack has gone through many iterations, starting originally as a humble Jupyter notebook. We introduced dbt in the stack first to simply prevent our dashboards from breaking constantly. Over time, we built around dbt and we can now extract and visualize data from any new open source community with just a few lines of code changes.

Join the chat in the #coalesce-open-source-communities channel ( If you’re not yet a member of dbt Community Slack, sign up at

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Srini Kadamati

Srini is a Data Scientist at Preset & a Developer Advocate for the Apache Superset project. He brings 7+ years of experience in data science and data science education, most recently at Dataquest.

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