From Big to Very Big Data — Why Normalization Is Needed in Big Data
summary
Discusses why normalization remains important in Big Data storage design: when initial data warehouses are built (requirements → data model → ETL), growth in data volume and especially data complexity over years can make them unmanageable. Describes problems caused by denormalized or brittle schemas in large-scale systems and argues for applying normalization principles to improve scalability and maintainability of Big Data stores.
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