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Explore common data enrichment patterns for streaming data and their implementation using Apache Flink in this 27-minute conference talk. Learn about enrichment scenarios involving static reference data, external APIs, and change data streams. Gain insights into Flink's internal state management for storing reference data. Discover how to choose the most suitable enrichment pattern for your use case, considering throughput and latency requirements. Walk away with a clear understanding of how to apply these patterns in your streaming architecture to enhance data accuracy, completeness, and decision-making capabilities.
