Data Swamp to Data Swimming Pool: Cleaning up the Mess
summary
Acryl Data demonstrates a concrete governance pipeline: inventory metadata from Postgres, MongoDB, Kafka, Airflow, S3, Spark, Snowflake, dbt, Great Expectations and Looker into data Hub, auto-select tables in the top 25 percent by query volume, label 91 matches as tier one, and require description, classification and explicit ownership. The recommended process is iterative: set goals, cut scope, drive action, measure and repeat; early wins appear in weeks (two months for buy‑in, three two‑week sprints to a case study).
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chapters (11)
- 0:00crunch
- 6:54Long Tail Companions' Modern Data Practice
- 11:46The Modem Data Swamp
- 15:01A Prerequisite: The Data Catalog
- 16:18Set Clear Goals
- 17:11Narrow the Scope
- 18:42Drive Incremental Action
- 21:56Measure Progress
- 23:44Setting Clear Goals
- 25:14Narrowing the Scope-Automated Scoping
- 27:23Driving Incremental Action
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