When you are going to implement data governance one key prerequisite is to work with a framework that outlines the key components of the implementation and ongoing program.
There are many frameworks available. A few are public while most are legacy frameworks provided by consultancy companies.
Anyway, the seven main components that you will (or should) see in a data governance framework are these:
- Vision and mission: Formalizing a statement of the desired outcome, the business objectives to be reached and the scope covered.
- Organization: Outlaying how the implementation and the continuing core team is to be organized, their mandate and job descriptions as well as outlaying the forums needed for business engagement.
- Roles and responsibilities: Assigning the wider roles involved across the business often set in a RACI matrix with responsible, accountable, to be consulted and to be informed roles for data domains and the critical data elements within.
- Business Glossary: Creation and maintenance of a list of business terms and their definitions that must be used to ensure the same vocabulary are used enterprise-wide when operating with and analyzing data.
- Data Policies and Data Standards: Documentation of the overarching data policies enterprise-wide and for each data domain and the standards for the critical data elements within.
- Data Quality Measurement: Identification of the key data quality indicators that support general key performance indicators in the business and the desired goals for these.
- Data Innovation Roadmap: Forecasting the future need of new data elements and relationships to be managed to support key business drivers as for example digitalization and globalization.
Other common components in and around a data governance framework are the funding/business case, data management maturity assessment, escalation procedures and other processes.
What else have you seen or should be seen in a data governance framework?
Liliendahl on Data Quality 