Data management refers to the set of practices, techniques, and tools for managing storage of and access to enterprise data assets while ensuring security and governance. While this definition is highly general, and data management sub-domains are full topics in themselves, it does encircle the fact that data management as a practice has grown exceptionally complex alongside those business use-cases that are incorporating ever more greater volumes and varieties of data. Due to this phenomenon, for many enterprises, it simply is not possible to conduct operations without a highly tuned data management system to collect, track, organize, and deliver the information that is critical to business processes.
The discipline of data management can be divided into two levels, a technical layer, and a non-technical layer. On one level, raw data is collected, transferred, processed, analyzed, and stored. But more and more the second layer, the non-technical level, is prioritized as the location where business users come into contact with the data efforts of the technical layer. At this level, business personnel using higher level dashboards can quickly glean insight into their everyday workflows.
Data management contains multiple subdomains, each specialized and complex. These subdomains broadly represent the priority disciplines in modern data management today.