30 Apr, 2021 / Victoria Gombert Article

The three functions of a data governance framework_

The nature of data in an organisation means it should be treated as a major asset that can be leveraged for success.

Data is often the basis of strategic and operational business decisions. The nature of data in an organisation means it should be treated as a major asset that can be leveraged for competitive advantage. A data governance framework is the process of taking a proactive approach to high-level management of data within an organisation, and addresses important key areas related to your data to ensure the integrity of data and business decisions.

A Data Governance Framework

The first step toward embedded data governance is developing a Data Governance Strategy. The next step is to create your Data Governance Framework.  A Data governance framework has three key elements:

  1. Policy
  2. Process
  3. Roles and Responsibilities

1. Data Governance Policy.

For successful data governance, the framework should have a high-level Policy document. The Policy document outlines the following things:

  • Scope of the Policy
  • Processes involved
  • Roles and responsibilities
  • Standard of data quality
  • Dimensions of data quality

Separate from the Policy document is the Operating Model. The Operating Model contains the detailed level account of the following things:

  • How the Policy will be implemented
  • Individual roles with a full account of responsibilities
  • Procedures to ensure data is of quality standards
  • Processes for events

The Operating Model is designed to be an operational document that is flexible and can be updated easily as the businesses data governance efforts evolve over the course of time.

The Policy document is a strategic level document that is designed to reflect business rules and hold governance and accountability over the organisation.

2. Data Governance Process.

The process function of the Data Governance Framework is designed to identify specific processes and outline what needs to occur when an event happens. The minimum subset of processes should involve:

  • Data Quality Reporting
  • Data Quality Issue Management
  • Master Data Management Process (if applicable)
  • Updating the Data Governance Programme

These processes will eliminate any uncertainty around what is to occur and provides a structured approach to data governance efforts. Through having a structured approach, data governance efforts such as data quality reporting will have consistent benchmarks and help improve the overall data quality within the organisation.

3. Data Governance Roles and Responsibilities.

The roles and responsibilities function of the Data Governance Framework is about ensuring the right people are selected for specific roles and understand their responsibilities in ensuring that data governance is followed in the organisation. The roles and responsibilities might be one person or a team approach depending on the size of the organisation. 

The key roles and responsibilities include:

  • Data Owner – accountable for the quality, authority and approval of a data set or data attribute (depending on the organisation).
  • Data Steward – supporting a data owner, making necessary changes and checking data quality reports.
  • Data Producer – responsible for the input of data into a source system.
  • Data Consumer – the people who use the data to operate and run the organisation.
  • Data Custodian – maintaining the data and ensuring the business rules are reflected on the source system.
  • Data Governance Manager – executive level sponsor who ensures the Data Governance Programme is being followed.

Collectively, the framework provides the foundational documents and core functions that need to be implemented in the organisation.

The final step is to implement, which can be the most challenging step. More on this to be released soon. 


This is an excerpt of the e-book Governance of Data in an Organisation by Victoria Calderwood, to be released soon.