
Best Practices for Implementing Data Governance Program
Implementing and maintaining a data governance program is challenging. Data governance best practices are derived from experience. Therefore, consider how other businesses implement and maintain their data governance process. It is a great idea to start small and move upwards. In this way, you can test different strategies and choose one that works smoothly with your business environment.
Data governance services like Ewsolutions recommend best practices based on the success they experienced with their clients. It allows you to get the most from your data governance program. You can even gain data governance training from Data Management Education experts.
Focus on an operational model
An operational or asset model outlines the business terms, roles, responsibilities, data domains, etc. of an organization. This can impact the functioning of processes and workflows of an organization. The operational model is the foundation of the data governance program. It establishes the framework based on the company. It can either be centralized or decentralized.
Recognize data domains
Determine data domain for every business line. It contains the following –
- Data owners
- Data dictionaries
- Business glossaries
- Data quality
- Business processes
- Standards & policies
- Report catalogs
- Systems & apps
- Data catalogs
Recognize crucial data features within data domain
Data domains touch myriads of apps and systems including critical data elements, key reports, business processes, etc. Never concentrate on every feature at once, but identify which ones are crucial for your business in the early phase.
Define control extents
Set control extents to sustain data governance program. It is an ongoing project that fuels decision-making as well as creates new business opportunities. The organization is made ready to fulfill business standards. The key activities of control measurements are –
- Define the automated workflow processes along with thresholds for review, approval, voting, problem resolution, etc.
- Apply workflow processes to data domains, crucial data elements, and governance structure.
- Program progress reporting
- Capture feedback via automated workflow processes
Promote continuous communication
Efficient communication via shared language is useful. Consider three aspects of data governance communication –
- Buy-in – Every leader needs to understand data value. Communicate how the data governance program will help and the risks if they don’t participate. Obtaining buy-in from money men helps to receive resources and funds as well as other department adopts the program with ease.
- Onboarding – Train every member connected with data about data governance value in detail.
- Adoption – Consistently communicate the importance of data governance so that everyday users will adopt the practice and technology.
Measure data governance goals
You need to measure data governance goals using specific metrics. It is an essential practice because you gain insight and a chance for improvement. Your KPI must be directly relevant to your company’s strategies and goals. Some areas to monitor are –
- Business glossary and data dictionary
- Access
- Adoption
- Issue management
- Data quality
- Policy compliance
- Reusability
- Scalability
- Financial ROI
These are some best practices associated with a data governance program that every organization big or small needs to follow. Depending on the sector there are distinct approaches. You can learn about them on the Data Management Education website.