Simplifying data flows
summary
Claims that Amazon tools remove pipeline plumbing: uses Zero ETL ingestion into an open SageMaker Lakehouse, ingesting relational (Aurora → Redshift), DynamoDB and Salesforce with 15‑minute sync windows (Aurora observed ~6–7 minute CDC lag) and Kinesis/Firehose for near‑real‑time. Demo wires three disparate sources and shows data discoverability via a catalog and marketplace—ingested metadata, published data products, and a data‑sharing flow that handles billions of small messages by moving them into Iceberg with automatic compaction. three sources in three minutes
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chapters (11)
- 0:00Introduction to simplifying data flows
- 1:48Why data drives business success
- 5:04Streamlining data flows overview
- 6:09SageMaker lakehouse foundation
- 8:37Zero ETL data ingestion explained
- 13:42Zero ETL patterns for databases
- 16:09Streaming data with Iceberg tables
- 17:55Live demo of three integrations
- 22:09Data sharing patterns and catalog
- 24:38Demo of data marketplace sharing
- 27:49Summary and key takeaways
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