Julia Schottenstein is the Product Manager @ dbt Labs. This is her session for the Open Source Data Stack Conference 2021

Julia Schottenstein is a Product Manager at dbt Labs. She was previously a Principal at NEA, a venture capital firm, and still serves on the board of Sentry and Metabase. She’s invested in more than a dozen open source, infrastructure, dev tool or data startups, and she co-hosts dbt Labs’ Analytics Engineering Podcast.

Transform: dbt
Learn about what it means to be an analytics engineer. dbt is a transformation workflow that lets teams quickly and collaboratively deploy analytics code following software engineering best practices like modularity, portability, CI/CD, and documentation. Now anyone who knows SQL can build production-grade data pipelines. We’ll spend time talking about the workflows dbt enables and give a short demo of how the platform works.

Register: https://tinyurl.com/776ny5rb

About the Event
The emergence of the modern data stack has seen a rapid spike in the number of data tools an organization can use to drive better decision making. Each tool has become highly specialized in its portion of the data lifecycle, plus tools that are open source are a powerful way for technology buyers to reduce exposure to vendor lock-in.

Control the end-to-end flow of customer data:
To guarantee data auditability
To allow data governance
To support consumer data privacy
To enable productive engineer workflows
By taking ownership and control over your data pipeline through open source, you can reduce the “trust surface area” for your customer data.

We are bringing together the building blocks of the open source data stack to demonstrate how teams can build a data stack that reflects their needs.

Learn about the data flow lifecycle, the modern data stack pipeline, how open source tools integrate and why data teams need help to move and transform data efficiently. Discover gems about ETL, ELT, reverse-ETL, and more with 7 speakers who are passionate about the solutions that data engineers, data analysts, data scientists, data managers and marketers need when dealing with customer data and customer success.

Register: https://tinyurl.com/776ny5rb