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.

In a world where data teams need agility, flexibility, and control over their pipelines, dlt (data load tool) steps in to simplify and empower the data engineering process. We’ll discuss how dlt integrates with other tools, to create seamless, end-to-end pipelines that are easy to configure and maintain. Perfect for data engineers, analysts, and anyone eager to embrace a future of composable, future-proof data workflows.