As development cycles grew more complex, ASML faced increasing challenges in realising value from their data platform. Maintaining the Bronze layer required significant effort, limiting the time available for innovation and new use cases.

To overcome these limitations, the RevoData team re-architected ASML’s ingestion framework to create a more efficient and flexible foundation. The improvements included the use of Autoloader for seamless ingestion, the adoption of native PySpark capabilities, and the decoupling of configuration and schema management to enable greater scalability. These changes were designed to reduce operational complexity and allow the organisation to focus more of its resources on higher-value work across the Silver and Gold layers.

The result is a significantly more scalable and maintainable ingestion framework that boosts performance while reducing manual overhead. With a streamlined architecture in place, ASML now has more freedom to innovate, accelerate development, and unlock new data-driven opportunities.

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