Hot-to-Cold Data Management: Infrastructure Requirements in the Age of AI - Seguridad Mania.com - España y América Latina

This rise of AI, deep learning, and modern demanding workflows has changed storage and infrastructure requirements. Organizations must have powerful solutions that can fuel demanding AI and data science workloads (hot data) on the front end, integrated with low-cost, secure private clouds to archive the massive amounts of data (cold data) to train these models on the back end—all while keeping data protected and secure. Data continually flows along the hot-to-cold continuum, and the infrastructure supporting this lifecycle must be flexible, automated, and simple to manage to keep up with the ever-changing nature of this data. Learn how AI is evolving the landscape of storage and infrastructure requirements, and the considerations for storing and managing hot and cold data to fuel AI initiatives.