How to Build a Workday‑to‑Azure Data Lake ETL Pipeline in 2026

Workday contains sensitive HR and workforce data but is positioned as unsuitable for direct analytics, so the guide recommends replicating it into Azure Data Lake Storage Gen2 for scalable reporting, machine learning, and integration with Databricks, Synapse, and Power BI. It proposes a governed Azure architecture using Bronze, Silver, and Gold storage layers, Azure Data Factory for orchestration, Key Vault and managed identities for credentials, and monitoring through Azure Monitor and Log Analytics. Incremental replication and change data capture are presented as preferable to recurring full extracts, with CData Sync offered as a connector for moving Workday data into ADLS Gen2. Raw data should be stored in partitioned Parquet files, transformed in Databricks with Delta Lake into standardized and business-ready datasets, and protected by quality checks, lineage tools, access controls, version control, and CI/CD practices. The guide also stresses testing at production scale, monitoring latency, errors, row counts, and costs, starting with dependable batch processing before adopting CDC, and designing Gold-layer schemas around actual stakeholder reporting needs.

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