Penguin Random House - Our Story: An Evolving Modern Data Stack With Snowflake
summary
Penguin Random House moves 37 TB from on‑prem to Snowflake and shuts off physical servers after a three‑month migration, cutting the infrastructure team burden (28 people) and claiming 36,000 hours saved in one year. The stack uses Fivetran, Airflow, dbt and GitLab for ingestion, orchestration and transforms, adds governance with Data.world, increases data sources by 164%, and pilots Snowpark + Anaconda for in‑place ML and MLops rather than exporting data.
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chapters (6)
- 0:00Legacy data challenges
- 2:23Modernizing with Snowflake
- 5:33The snowflake platform
- 9:15Migration and evolution
- 13:31Impact and future vision
- 17:19Advanced data capabilities
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