The article discusses the development of a metadata-driven ETL framework utilizing Azure Data Factory. Aimed at streamlining the integration of various data sources like databases, cloud apps, and file systems, the architecture addresses complexity and inefficiency found in traditional ETL processes. By leveraging a metadata repository, the framework ensures flexibility and scalability, allowing for rapid adaptation to changing data requirements without extensive manual intervention or rework. The author shares insights into design decisions and the solutions implemented to navigate the challenges faced during development.
A metadata-driven ETL framework enhances scalability and security in integrating various data sources through Azure Data Factory, reducing manual rework.
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