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ETL (Extract, Transform, Load)

ETL (Extract, Transform, Load) is the process of extracting data from source systems, transforming it to meet the requirements of the destination system — by cleaning, standardising, enriching, and applying business rules — and loading the transformed data into the destination, typically a data warehouse or reporting database. ETL is the foundational data integration process that makes heterogeneous operational data usable for consistent, cross-system reporting and analysis.

Why This Matters

Most organisations run multiple operational systems — ERP, CRM, billing, payroll, logistics — each with its own data formats, naming conventions, and business rules. ETL is what brings this disparate data together into a unified, consistent form suitable for cross-system reporting. The quality of the ETL layer — how accurately business rules are applied, how completely data is extracted, how consistently transformations are executed — directly determines the quality and consistency of the management information produced from the data warehouse.

Where This Fits

This term sits within the BI & AI area of Performance & Control.

To be added when relevant Knowledge Hub articles are published

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