This talk unveils our design journey to streamline the ingestion of CDC changes into a data warehouse, enabling rapid data availability for users. We leverage Qlik to stream CDC events to Kafka, harness Dataflow’s processing power, and store the transformed data in BigQuery for efficient analysis.
We’ll walk through our iterative design process, showcasing how Apache Beam’s flexibility allowed us to address business requirements. We’ll highlight key architectural decisions, performance optimizations, and lessons learned along the way.
This blueprint serves as a valuable resource for others seeking to simplify their CDC ingestion pipelines and accelerate time-to-insight for their data-driven initiatives.