Data management is the process of gathering, storing, and using data in a safe, efficient, and cost-effective manner. The purpose of data management is to assist individuals, organisations, and connected objects in optimising their data usage within the constraints of policy and legislation in order to make choices and conduct actions that optimise the organization's advantage. A strong data management strategy is more critical than ever as businesses increasingly depend on intangible assets to produce value.
Today’s organizations need automated data management that enables them to handle data efficiently across varied yet unified data tiers. Data management systems are built upon data management platforms and may comprise databases, data lakes and warehouses, big data management systems, and data analytics.
All of these components operate in concert as a "data utility" to provide an organisation with the data management skills it requires for its applications, as well as the analytics and algorithms that use the data generated by those apps.
While modern technologies assist database administrators (DBAs) in automating many conventional administration duties, human intervention is often necessary due to the scale and complexity of the majority of database installations.
When physical intervention is necessary, the likelihood of making a mistake rises.
The autonomous database's primary goal is to eliminate the need for manual data administration.