Open source data platforms are the rising tide that lifts all ships by sharing invaluable wisdom, building goodwill, and accelerating the growth of the broader data community. That said, it can be difficult to open source data and analytics projects because of the risk of leaking sensitive information or bespoke business logic. So, how do you get started?
Tim Castillo will share a detailed look into how he and the data team at Dagster Labs successfully open-sourced their data platform, including the cultural shifts required to get buy-in from leadership, the technical implementation put in place to ensure ongoing compliance, and beyond. He'll share why it was a worthwhile undertaking for the team and organization alike, the technical workflows they put in place to retain trust, and the benefits they've seen since open-sourcing their data platform.
Data engineers, analytics engineers, and data platform engineers will learn how to reference open source to build better data platforms, pipelines, and products and will leave with a pragmatic set of skills to kickstart a conversation with the rest of their team on how to use and contribute to the data community through open source.
Tim is a data engineer and developer advocate at Dagster Labs. Previously, he was a data engineer and consultant for companies ranging from startups to Fortune 500s. Currently, Tim has been continuing this work by applying his experience to educate data practitioners at scale on how to build resilient and scalable data platforms.