Designing a Real-Time Event-Driven Data Lake with Change Data Capture (CDC) and Materialized Views Designing a Real-Time Event-Driven Data Lake with Change Data Capture (CDC) and Materialized Views In modern data architectures, teams often struggle to balance freshness, scalability, and cost when turning raw data into actionable insights. This guide presents a practical approach to building a real-time, event-driven data lake that ingests change data capture (CDC) streams, materializes views in near real-time, and provides a clean separation between ingestion, storage, and query layers. The design emphasizes reliability, observability, and cost-conscious scalability, with concrete architecture, data models, and example code.…