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Many information professionals today are watching the burgeoning growth in data generation overwhelm their operational data stores. Traditional architectures struggle with large data volumes and unstructured data, such as information gleaned from log data or social media, and the amount of data these data stores must ingest and process today is creating performance bottlenecks. This is unacceptable in the current technological landscape, and organizations are scrambling to maintain an efficient operational data store (ODS) as the amount of information available—and necessary— to perform business-critical analyses steadily grows.

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