Data management encompasses pretty much all aspects of controlling data as a valuable source of information. It includes starting procedures to accumulate, collect, store, transform and look after data — all considering the goal of delivering high-quality organization outcomes which can be trusted.
The idea of managing info as a tool dates back towards the first its heyday of information technology, when IT experts recognized that computers reached incorrect conclusions when they had been fed erroneous or insufficient data. After a while, mainframe-based hierarchical sources helped to formalize the process of data managing, which is now viewed as an important component to a firm’s overall THAT infrastructure.
A number of criteria may be used to measure data quality, according to industry by which an organization works and the position that info plays in its goals. Some examples include completeness, consistency and uniqueness. Completeness measures if all needed values can be obtained — for example , if your team needs a customer’s last name to ensure their website mailing is resolved correctly, the data source must include that bit of data. Consistency ensures that info values continue to be the same as they move among applications and networks, while uniqueness makes sure that duplicate data items are certainly not stored two times in different places.
Companies that excel at data management experience a well-defined set of data processes that help them recognize, analyze and interpret business problems and opportunities in a timely trend – to enable them to take action quickly and with certainty. In addition to improving decision-making, info management can reduce risk and help firms meet regulating requirements.