Data Governance involves organizing, managing, and monitoring the integrity and security of data in an enterprise’s system. It requires businesses to establish policies and frameworks to facilitate these processes, ensuring that any new or existing data complies with current internal and external regulatory standards such as GDPR. Data Governance metrics help measure the efficacy and impact of a Data Governance program and show whether it is aligned with the organization’s business strategy.
What Are Data Governance Metrics?By on
Types of Data Governance Metrics:
The Data Governance metrics organizations should use will depend on the issues they want to resolve. There are broad buckets under which these metrics can be categorized:
- Data Quality: Improving Data Quality mitigates compliance risk and helps leaders make more reliable decisions. Key Data Quality metrics include data accuracy, completeness, consistency, and integrity, as well as the number of data issues found and resolved.
- Data Literacy: The more an organization prioritizes Data Literacy, the more its stakeholders understand the value of data – and the more likely they are to support long-term Data Governance goals.
- Data Ownership and Accountability: Who are the data owners (aka those accountable for the data in a specific data domain) and how successful have they been at maintaining data reliability and adhering to data-related laws?
- Business Value: It’s essential to effectively communicate business value to stakeholders, with metrics such as cost savings, revenue growth, and cost avoidance (which can be achieved by complying with regulations, for example) due to a Data Governance initiative.
- Tracking the progress of an ongoing Data Governance initiative
- Documenting the business benefits of Data Governance
- Maintaining stakeholder buy-in by demonstrating program successes
- Highlighting Data Governance challenges and how to overcome them
- Conveying the potential dangers and costs of not following Data Governance processes
- Encouraging a greater focus on compliance with regulatory standards
- Making Data Management easier by implementing a governance framework
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