Building an Enterprise Data Lake Architecture on AWS
summary
Claims that a full serverless enterprise data lake can be deployed end-to-end in a short workshop, using Kinesis Data Firehose to stream sample events into S3, cataloging with AWS Glue (crawler, ETL jobs, data catalog), querying with Amazon Athena, and visualizing with Amazon QuickSight. Notes that 90% of ETL is still hand‑coded, shows pre‑deployed pieces (Cognito/Lambda) and sandbox accounts, and the demo ingest, transform and dashboard all run successfully.
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chapters (13)
- 0:00Introduction to workshop
- 1:32Workshop agenda overview
- 4:43Why analytics on AWS
- 7:13Modern data architecture
- 10:44Data lake fundamentals
- 17:25Serverless data lake benefits
- 21:53Lab one recap and break
- 22:14Data ingestion with Kinesis
- 27:48AWS Glue ETL platform
- 34:10Amazon Athena for queries
- 40:10Amazon QuickSight dashboards
- 46:14Lab two and three overview
- 48:06Q&A and closing
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