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This page describes the key functions of implementing effective data governance and management.

Key Functions

In a small government, one person may have to take on multiple functions, while some functions can be contracted out. In a larger government, it may be possible to hire staff for each of the required functions.

  • Data governing body: The decision makers with oversight responsibility for data, including developing and implementing data governance processes. In a smaller government, this may be a single person; in larger governments it may be a committee that includes senior managers from various departments responsible for socioeconomic outcomes.
  • Privacy officer: For most governments, it is appropriate to have a single authority for privacy and data usage considerations. This authority is responsible for evaluating data usage against privacy regulations, collaborating with legal advisors, and responding to concerns from citizens about how their personal information is being collected and used.
  • Data stewardship or custodianship: Data stewards and custodians are the keepers of the data. They implement the decisions of the data governing body. The term “custodianship” tends to refer to IT functions whereas “stewardship” refers to non-IT functions. Data stewardship or custodianship activities include:
    • Understanding the data needs of the government.
    • Understanding how data is (or will be) used.
    • Contributing to policy development.
    • Contributing to determining what data will be collected.
    • Creating clear data definitions and standards.
    • Ensuring policies are followed.
    • Monitoring data quality.
    • Reporting back to the governing body.
  • Data management: Data management activities include[1]:
    • Data entry and storage.
    • Data quality assurance.
    • Metadata entry and documentation (see the Data Quality section).
    • Distributing data to users.
    • Assisting data users.
  • Data analysis: Data analysis involves using data to produce organized information and knowledge. Data analysis activities include:
    • Defining the gap in knowledge to be filled.
    • Identifying data needed and requesting access to it from the data manager.
    • Developing and carrying out an analysis plan.
    • Producing reports and presentations to translate the analysis into information and knowledge.
  • Data Communication: Translating data into knowledge and integrating with Indigenous ways of knowing and doing. Knowledge translation includes communicating knowledge to knowledge users through story-telling and visualizations.
  • Database development and administration: The analysis, design, creation, and maintenance of databases.
  • IT management: IT management ensures IT systems follow data management policies. IT management is key to implementing data storage and security policies, for example, backups and access rules.



[1] DataBC. 2013. A Guide for Data Custodians and Data Managers.

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