Principles of Modern Data Platforms

Overview

A half-day overview of how a modern data platform is built: ingestion, storage, processing, governance, and AI architectures, and how those pieces fit together to turn data into data products.

What you'll cover

• ▸The pyramid of needs: infrastructure, pipelines, operations, insights
• ▸Data platform versus data products, and the maturity curve
• ▸Ingestion: batch, streaming, connectors, data contracts
• ▸Storage: data warehouse, data lake, lakehouse and open table formats, event hubs, vector databases
• ▸Processing and insights: SQL and dbt, Python and Spark, streaming analytics, MLOps
• ▸Data governance in practice: catalogs, purpose-based access control, data contracts
• ▸AI architectures: semantic layer, RAG, MCP, agents

What you'll be able to do

No skills listed.