Get ready to ingest data and transform it into ready-to-use datasets using Python. We'll share a no-nonsense approach for developing and testing data connectors and transformations locally. Moving to production will be a matter of tweaking your configuration. In the end, you get a simple dataset interface to build dashboards & applications, train predictive models, or create agentic workflows. This workshop includes two guest speakers. Brian teach how to leverage AI IDEs, MCP servers and LLM scaffoldings to create ingestion pipelines. Elvis will show how to interactively define transformations and data quality checks.
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Speaker
Brian Douglas
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talks
Head of Developer Experience
Continue
Brian is Head of Developer Experience at Continue. He’s been involved in developer experience for 8+ years (GitHub, Netlify, Linux Foundation, Heavybit). Continue lets developers build and run custom agents across their IDE, terminal, and CI.
Bio from: Small Data SF 2025
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