How to Create and Implement a Data Governance Policy

Data-driven companies need to create and implement a data governance policy to make the most effective use of enterprise information resources. A viable data governance policy assists in the implementation of data governance throughout a business.

What Is A Data Governance Policy?

A data governance policy describes the guidelines an organization imposes internally, for effectively managing and using its data assets. The guidelines define specific standards for how data quality and accuracy are maintained across all areas of a business.

Key Elements of a Data Governance Policy

• Guidelines for data quality and accuracy
• Policies on how data is used, accessed, and secured
• Roles and responsibilities for implementing and monitoring data governance

A data governance policy is a key component of a robust data governance framework. A framework addresses the complete data governance program, whereas a data governance policy is more concerned with people and processes. A data governance policy is an integral part of shaping an organization’s data culture.

Why Is A Data Governance Policy Important?

Implementing a data governance program can be a daunting task. Data governance often requires a substantial shift in the corporate culture regarding enterprise data. This kind of change cannot be accomplished based on vague initiatives. A well-defined roadmap is necessary to keep everyone in the organization moving in the same direction.

Benefits of a Well-Defined Data Governance Policy

• Provides a centralized repository of processes for governance implementation
• Ensures alignment across departments on data handling procedures
• Increases the likelihood of achieving governance goals
• Eliminates misunderstandings between different departments

Without concurrence on how data is handled, a governance program will never achieve its maximum value. Documented policies can be instrumental in ensuring the success of a data governance program.

How Do I Create A Data Governance Policy?

Creating a data governance policy requires a methodical approach that involves the following steps:

1. Communicate the Value of Data Governance

• Outline the business benefits of data governance to decision-makers and stakeholders.
• Demonstrate the importance of its implementation for business success.

2. Form a Data Governance Team

• Determine roles and responsibilities.
• Define who is responsible for specific components of the governance program.

3. Assess the Current State of Data Governance

• Evaluate the company’s existing data governance practices.
• Gather input from stakeholders to align program direction and gain support.

4. Draft the Policy

• Create the initial draft of the policy.
• Ensure it is reviewed by stakeholders and revised as needed.

5. Disseminate the Policy

• Share the finalized policy with all relevant stakeholders across the organization.

6. Define Performance Metrics

• Establish key metrics to measure the policy’s success against its goals.

7. Review and Update the Policy Regularly

• Treat the data governance policy as a living document.
• Update the policy in response to evolving business needs and program goals.

Can I Use A Data Governance Policy Template?

Data governance policy templates are available and may seem like a good way to streamline policy development. However, templates may overlook unique aspects of a company’s data resources and culture, which can reduce the effectiveness of the policy.

A Customized Approach is Better

• Instead of relying on a template, focus on adapting the policy to the specific needs of the business. Consider the following elements:

1. Identify Key Data Roles

• Identify individuals such as data stewards and data owners who hold crucial roles across the organization.

2. Conduct and Maintain a Data Inventory

• Maintain an up-to-date data inventory by adding new data sources and removing obsolete ones regularly.

3. Define Purpose and Develop Data Policies

• Clarify why information is collected and create policies around the creation, management, and deletion of enterprise data.

4. Assign Data Quality Responsibility

• Designate the appropriate personnel to be responsible for ensuring data quality.

5. Define Data Access Permissions

• Specify who has access to certain systems and data, outlining clear access permissions for different types of data.

6. Create Data Security Policies

• Establish guidelines for how data will be accessed and shared securely.

7. Set Metric-Based Goals

• Develop measurable goals for each of the items above to assess the success of the data governance program.

How Do I Implement A Data Governance Policy?

Implementing a data governance policy and the ensuing data governance program is not something that can be done with a single application. There are no data governance programs available for a quick fix. Data governance requires collaboration across the organization and tools that can help identify the enterprise data resources that will be governed.

Tools for Data Governance Implementation 

The ER/Studio family of data modeling tools is a valuable solution for creating a data governance policy and identifying said data resources. The three related applications address a range of aspects in data governance policy development.

ER/Studio Business Architect

Business Architect maps the relationships between the people, processes, and data that need to be understood to develop a viable data governance policy.

• Key Features:
  • Maps relationships between people, processes, and data.
  • Helps in policy development.

ER/Studio Data Architect

ER/Studio Data Architect lets teams build out enterprise data models, discover and document data assets, and create a data catalog to support governance activities.

• Key Features:
  • Builds enterprise data models
  • Discovers and documents data assets
  • Creates data catalog

Try ER/Studio Data Architect for Free!

ER/Studio Enterprise Edition

ER/Studio Enterprise Edition is a collaborative tool that enables an organization to share data models and build the common data vocabulary necessary for successful data governance. Its shared repository supports model consistency and keeps all stakeholders informed of changes. It furnishes the required functionality to build a strong foundation for a data governance program.

• Key Features:
  • Enables collaboration across teams
  • Supports shared repository for model consistency
  • Keeps stakeholders informed of changes

Request a free demo of ER/Studio Enterprise Edition!

Conclusion

Organizations developing a data governance policy should investigate the features available in ER/Studio. The tools will help companies meet the underlying business goals of data governance.