How does data governance impact data quality?

Data governance is the framework of policies, processes, and controls that ensures data is accurate, complete, reliable, and secure. It plays a crucial role in maintaining high data quality within an organization.

Relationship between data governance and data quality

Effective data governance practices directly impact data quality in several ways:

1. Data Accuracy

Data governance ensures that accurate data is captured, stored, and used across the organization. By defining data standards, policies, and processes, data governance eliminates errors and inconsistencies in data, leading to improved accuracy.

2. Data Completeness

Data governance defines rules for data collection and validation, ensuring that data is complete and not missing critical elements. This helps in preventing incomplete or partial data sets that could impact decision-making.

3. Data Reliability

Through data stewardship and compliance with data policies, data governance ensures that data is reliable and trustworthy. It establishes mechanisms for data validation, consistency checks, and establishes data integrity, leading to improved data reliability.

Overall, effective data governance practices are essential for enhancing data quality, which is crucial for informed decision-making, regulatory compliance, and overall business success.