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ETL template for usage analytics
Refactored a fragmented set of analytics pipelines into a reusable Python template with consistent ingestion, transformation, testing, and operational behaviour.
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Refactored a fragmented set of analytics pipelines into a reusable Python template with consistent ingestion, transformation, testing, and operational behaviour.
Five MERGE patterns that solved real problems for me: idempotent upsert, soft delete, late-arriving data, deduplication on ingest, and the slowly-changing-dimension type-2 case. Plus the performance gotchas that bit me first.