DS11 Manage Data

Effective data management requires identifying data requirements. The data management process also includes the establishment of effective procedures to manage the media library, backup and recovery of data, and proper disposal of media. Effective data management helps ensure the quality, timeliness and availability of business data.

Control over the IT process of Manage Data that satisfies the business requirement for IT of
  • optimizing the use of information and ensuring that information is available as required
by focusing on
  • maintaining the completeness, accuracy, availability and protection of data
is achieved by
  • Backing up data and testing restoration
  • Managing on-site and off-site storage of data
  • Securely disposing of data and equipment
and is measured by
  • Percent of user satisfaction with availability of data
  • Percent of successful data restorations
  • Number of incidents where sensitive data were retrieved after media were disposed
Management of the process of Manage Data that satisfies the business requirement for IT of optimizing the use of information and ensuring that information is available as required is:

1 Non-existent
2 Initial/Ad Hoc
3 Repeatable but Intuitive
4 Defined
5 Managed and Measurable
6 Optimized


Benchmarks/Guidelines for Scoring

1 Non-existent when
Data are not recognized as corporate resources and assets. There is no assigned data ownership or individual accountability for data management. Data quality and security are poor or non-existent.
2 Initial/Ad Hoc when
The organization recognizes a need for effective data management. There is an ad hoc approach for specifying security requirements for data management, but no formal communications procedures are in place. No specific training on data management takes place. Responsibility for data management is not clear. Backup/restoration procedures and disposal arrangements are in place.
3 Repeatable but Intuitive when
The awareness of the need for effective data management exists throughout the organization. Data ownership at a high level begins to occur. Security requirements for data management are documented by key individuals. Some monitoring within IT is performed on data management key activities (e.g., backup, restoration, disposal). Responsibilities for data management are informally assigned for key IT staff members.
4 Defined when
The need for data management within IT and across the organization is understood and accepted. Responsibility for data management is established. Data ownership is assigned to the responsible party who controls integrity and security. Data management procedures are formalized within IT, and some tools for backup/restoration and disposal of equipment are used. Some monitoring over data management is in place. Basic performance metrics are defined. Training for data management staff members is emerging.
5 Managed and Measurable when
The need for data management is understood, and required actions are accepted within the organization. Responsibility for data ownership and management are clearly defined, assigned and communicated within the organization. Procedures are formalized and widely known, and knowledge is shared. Usage of current tools is emerging. Goal and performance indicators are agreed to with customers and monitored through a well-defined process. Formal training for data management staff members is in place.
6 Optimized when
The need for data management and the understanding of all required actions is understood and accepted within the organization. Future needs and requirements are explored in a proactive manner. The responsibilities for data ownership and data management are clearly established, widely known across the organization and updated on a timely basis. Procedures are formalized and widely known, and knowledge sharing is standard practice. Sophisticated tools are used with maximum automation of data management. Goal and performance indicators are agreed to with customers, linked to business objectives and consistently monitored using a well-defined process. Opportunities for improvement are constantly explored. Training for data management staff members is instituted.