Data Management is the practice of collecting, keeping, and using data securely, efficiently, and cost-effectively. The goal of data management is to help people, organizations, and connected things optimize the use of data within the bounds of policy and regulation so that they can make decisions and take actions that maximize the benefit to the organization. A robust data management strategy is becoming more important than ever as organizations increasingly rely on intangible assets to create value.
Managing digital data in an organization involves a broad range of tasks, policies, procedures, and practices. The work of data management has a wide scope, covering factors such as how to
* Create, access, and update data across a diverse data tier
* Store data across multiple clouds and on premises
* Provide high availability and disaster recovery
* Use data in a growing variety of apps, analytics, and algorithms
* Ensure data privacy and security
* Archive and destroy data in accordance with retention schedules and compliance requirements
A formal data management strategy addresses the activity of users and administrators, the capabilities of data management technologies, the demands of regulatory requirements, and the needs of the organization to obtain value from its data.
Source: ORACLE
Source: TU Delft Data Steward Teams
"Data Management refers to the storage, access and preservation of data produced from a given investigation. Data management practices cover the entire lifecycle of the data, from planning the investigation to conducting it, and from backing up data as it is created and used to long term preservation of data deliverables after the research investigation has concluded..."
Source: CASRAI. (n.d.). Research Data Management Glossary.
Source: McMaster University Library
