Guys, so our data team here in the US is dealing with a BigQuery to BigQuery pipeline that's gotten pretty messy. Anyone set up a clean ETL process for this specific route and found something that handles schema changes without constant manual intervention?

The schema drift problem is what gets most teams eventually. Pipelines that work fine for months suddenly break when an upstream table gets modified. Building in proper schema validation from the start saves a lot of painful debugging later.

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Schema drift is exactly what nobody thinks about until it's already causing problems in production. BigQuery ETL within the same ecosystem sounds straightforward on paper but the edge cases around incremental loads, deduplication and handling structural changes upstream are where things get complicated fast. Purpose built tooling for this specific route handles these scenarios more predictably than something patched together manually. Worth understanding what's available before committing to an architecture. More on how this pipeline works is here http://datrise.com/en/pipeline/bigquery-to-bigquery

jacob wrote: ((((((  very bed!!!! Why ruin someone else's work!

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