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Article submission for a future issue.
Link: https://www.dsstream.com/post/etl-process-optimization
Why this piece: Twelve ETL tuning techniques with SQL examples, each paired with the failure it tends to introduce, plus a tool comparison table (Airflow, dbt, Spark, Snowflake and others) and a 30-60-90 day rollout plan. The techniques are tool-agnostic: incremental loads and CDC, pushdown and bulk loading, partition pruning, skew handling, set-based SQL, columnar formats, indexing, caching, batch vs streaming, orchestration with retries and lineage, in-pipeline data quality checks, compute cost controls.
Disclosure: the article is published on a company engineering blog (DS Stream); the text itself does not pitch any product or service. Happy to adjust the review snapshot or tags.