This whitepaper challenges traditional ETL-heavy architectures and advocates for smarter, query-driven data transformation strategies. It explains how modern distributed SQL engines enable transformation at query time, reducing the need for costly and complex pipeline engineering. By avoiding unnecessary data replication and leveraging schema-on-read techniques, enterprises gain flexibility and faster experimentation cycles. The paper highlights cost savings, improved scalability, and reduced technical debt. It concludes that modern analytics stacks should prioritize federation and transformation-in-place to improve agility and optimize infrastructure investment.

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