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Optimizing Large-Scale ETL Pipelines Using Medallion Architecture on Azure Data Lake

Journal of Artificial Intelligence and Big Data | Vol 1, Issue 1

Table 1. Rollout phase summary

PhaseScopeMain success criteriaKey risk controls
Phase 1 - Pilot BUSingle BU, selective assetsSSO works, core catalog policies enforcedRollback criteria, limited blast radius
Phase 2 - Broaden scopeAdditional data/system combinationsCross-workspace sharing and controls provenProgressive validation, monitored cutover
Phase 3 - Production landing zoneOperational governance modelCI/CD artifact promotion and support process liveEnvironment separation, auditable deployment
Phase 4 - Continuous optimizationWider adoption and economics tuningPolicy tuning, quality stability, cost controlAlert thresholds, role refinement, lifecycle cleanup