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Autonomous Data Management: AI Comes to Data Management
Autonomous Data Management (ADM) is the application of AI to standard Data Management. The result is a kind of Data Management that is smarter and easier to use, or at least that’s what the marketing would have you believe. The ‘Autonomous’ part of the name implies dynamic self-learning that can adjust to changes in the environment.
Some areas where standard Data Management can be made smarter is with the general management of the application — self-provisioning, self-optimizing, self-healing, vigilant protection from security threats, and federation of data across not only different applications but different cloud and on-premise environments. Those are some of the promises of ADM.
Oracle has advertised their ‘Autonomous Database’ offering for some number of years as being able to perform self-maintenance, like patching, upgrades, and tuning — without human intervention. “Autonomous Data Management” is now also a buzzword used heavily by vendors like Veritas and Informatica, although Informatica is more focused on Master Data Management.
Mark Nutt, Senior Vice President at Veritas, said that “when Autonomous Data Management takes over, AI can enable proactive decision making and policy application at a much more granular level. It can learn the idiosyncrasies of different data types and apply whatever storage, protection or deletion policies that make sense. So, when new data is created it will automatically be protected, be stored securely, have access limited, and be deleted at the right time.”
