When to Use a Data Lakehouse
Organizations today generate huge volumes of data from applications, sensors, transactions, and customer interactions. Traditionally, this data was split between data warehouses for structured analytics and data lakes for raw, unstructured information, but each comes with limitations. Warehouses are expensive and rigid, while lakes can become messy and unreliable. The data lakehouse was created to […]
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