Data managing encompasses each and every one aspects of handling data as a valuable resource. It includes creating procedures to accumulate, collect, store, convert and preserve data — all with the goal of delivering high-quality business outcomes that may be trusted.

Thinking about managing info as a source dates back towards the first blooming of information technology, when IT specialists recognized that computers reached incorrect findings when they were fed erroneous or insufficient data. After a while, mainframe-based hierarchical sources helped to formalize the data control, which is now deemed an important a part of a firm’s overall THIS infrastructure.

Numerous criteria can be used to measure data quality, depending on the industry by which an organization works and the role that info plays in the goals. A few examples include completeness, consistency and uniqueness. Completeness measures if all expected values are available — for instance , if your workforce needs a customer’s last name to make certain reproworthy emailing is tackled correctly, the repository must comprise that little bit of data. Regularity ensures that data values continue to be the same as they will move between applications and networks, while uniqueness guaruntees duplicate info items are not really stored two times in different locations.

Companies that excel at data management experience a clear set of info processes that help them distinguish, analyze and interpret business problems and opportunities in a timely fashion – to allow them to take action quickly and confidently. In addition to improving decision-making, data management can reduce risk and help businesses meet regulating requirements.