Zaloni’s white paper defines a data lake as a centralized repository that stores all data—structured or unstructured—in its native format for flexible, scalable analysis. Unlike traditional data warehouses, data lakes reduce upfront processing and schema constraints. Key features include distributed storage, orchestration tools like YARN, and workflows for easy access. Common use cases are EDW augmentation, agile analytics, enterprise reporting, and fraud detection. With proper governance, data lakes help eliminate silos, reduce costs, improve compliance, and enable real-time insights across industries.

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