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Storage for AI and Analytics Data Pipeline - Optimize your storage architecture for every stage of your AI and Analytics data pipeline and models
Don Wilson, HPE
GTC 2020
Business insights are at the core of any digital transformation, as they're the key to increase competitiveness and operational efficiency, and to improve customer services. But AI applications are extremely demanding, as they require a broad spectrum of storage capabilities to support continuous data ingest streams, data transformation, model training, inferencing, and archival—each having distinct throughput, latency, capacity, and scalability requirements. We'll cover the HPE storage architecture blueprint, articulating a storage infrastructure capable of satisfying all AI and analytic requirements.