Scope of Data Management
There are four areas of management included within the scope of Data/Information Management:
- Management of data resources: the governance of information in the organization must ensure that all these resources are known and that responsibilities have been assigned for their management, including ownership of data and metadata. This process is normally referred to as data administration and includes responsibility for:
- Defining information needs
- Constructing a data inventory and an enterprise data model
- Identifying data duplication and deficiencies
- Maintaining a catalogue/index of data/information content
- Measuring the cost and value of the organization’s data.
- Management of data/information technology: the management of the IT that underpins the organization’s information systems; this includes processes such as database design and database administration. This aspect is normally handled by specialists within the IT function – see the Service Operation publication for more details.
- Management of information processes: business processes will lead to IT services involving one or other of the data resources of the organization. The processes of creating, collecting, accessing, modifying, storing, deleting and archiving data – i.e. the data lifecycle – must be properly controlled, often jointly with the applications management process.
- Management of data standards and policies: the organization will need to define standards and policies for its Data Management as an element of an IT strategy. Policies will govern the procedures and responsibilities for Data Management in the organization; and technical policies, architectures and standards that will apply to the IT infrastructure that supports the organization’s information systems.
The best practices scope of the Data Management process includes managing non-structured data that is not held in conventional database systems – for example, using formats such as text, image and audio. It is also responsible for ensuring process quality at all stages of the data lifecycle, from requirements to retirement. The main focus in this publication will be on its role in the requirements, design and development phases of the asset and Service Lifecycle.
The team supporting the Data Management process may also provide a business information support service. In this case they are able to answer questions about the meaning, format and availability of data internal to the organization, because they manage the metadata. They also are able to understand and explain what external data might be needed in order to carry out necessary business processes and will take the necessary action to source this.
Critically, when creating or redesigning processes and supporting IT services, it is good practice to consider re-using data and metadata across different areas of the organization. The ability to do this may be supported by a corporate data model – sometimes known as a common information model – to help support re-use, often a major objective for data management.