etl-elt-and-modernization-strategy
Guides agents through ETL, ELT, and transformation-modernization decisions. Use when choosing execution boundaries, redesigning transformation layers, or moving from legacy ETL estates to warehouse- or lakehouse-centered ELT patterns.
Works with
--- name: etl-elt-and-modernization-strategy description: Guides agents through ETL, ELT, and transformation-modernization decisions. Use when choosing execution boundaries, redesigning transformation layers, or moving from legacy ETL estates to warehouse- or lakehouse-centered ELT patterns. license: MIT --- # ETL ELT And Modernization Strategy ## Overview Use this skill when the hard part is not a single job, but deciding where transformations should run and how a data estate should modernize over time. It helps agents reason about `ETL` versus `ELT`, pushdown versus external compute, orchestration boundaries, migration sequencing, and proof of parity during modernization. ## When to Use - choosing between `ETL`, `ELT`, or hybrid transformation patterns - moving from legacy ETL tools into warehouse, dbt, Spark, or lakehouse execution - redesigning ingestion and transformation boundaries across raw, curated, and publish layers - reducing operational sprawl caused by duplicate transformation logic - modernizing batch-first estates without breaking existing delivery expectations Do not assume `ELT` is always better just because the warehouse is powerful. ## Workflow 1. Define the transformation problem clearly. Clarify: - source latency and volume - data quality expectations - transformation complexity - cost sensitivity - publish or consumption latency 2. Map the current execution estate. Include: - where extraction happens - where transformations happen today - what logic is duplicated across tools - where lineage or observability breaks - what jobs are hardest to change safely 3. Choose the right execution boundary. Consider: - `ETL` when data must be reshaped or protected before landing - `ELT` when warehouse or lakehouse pushdown improves maintainability and scaling - hybrid patterns when extraction, privacy controls, or heavy preprocessing must happen before durable load 4. Plan the modernization path. Decide: - what stays temporarily on the old path - what moves first - how parity will be measured - how cutover and rollback will work 5. Prove the new shape operationally. Require: - reconciliation evidence - cost and performance review - lineage continuity - ownership and support readiness ## Common Rationalizations | Rationalization | Reality | | --- | --- | | "Everything should become ELT." | Some workloads still need pre-load shaping, masking, or protocol-specific extraction controls. | | "The ETL tool is the problem." | The real issue may be unclear ownership, poor contracts, or duplicated logic across layers. | | "We can rewrite all transformations at once." | Big-bang modernization usually breaks parity, runbooks, and downstream trust. | ## Red Flags - the same business logic exists in extraction jobs, Spark, and warehouse SQL - ETL versus ELT is chosen by tool preference instead of workload needs - modernization plans skip parity, cutover, or rollback - sensitive fields are moved into ELT layers without revisiting controls ## Verification - [ ] The transformation boundary matches the real workload constraints - [ ] ETL, ELT, and hybrid choices are explicit rather than assumed - [ ] Modernization sequencing, parity proof, and rollback are defined - [ ] Cost, lineage, controls, and support ownership were considered together
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