Effective Data Governance: Benefits and Challenges

A well-implemented data governance framework can help organizations improve regulatory compliance, ensure consistent data definitions, solve data analytics and reporting issues, and reduce costs. However, there are a number of challenges that organizations must overcome in order to implement effective data governance.

Effective Data Governance

Data governance is the control and oversight of an organization's data management and datasets, including roles, responsibilities, and processes for ensuring accountability and ownership. A solid data governance framework enables an organization to manage its data as a strategic asset.

Benefits of effective data governance:

• Improve regulatory compliance: Data governance helps organizations to comply with regulations such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA).
• Consistent data definitions: Data governance ensures that data is defined and used consistently across the organization. This improves the quality and accuracy of data analytics and reporting.
• Solve data analytics and reporting issues: Data governance helps organizations to identify and resolve issues with data analytics and reporting. This leads to better decision-making.
• Reduce costs: Data governance can help organizations to reduce costs by eliminating errors and duplicates in data.
  
  

Typical challenges without solid data governance:

• Data entry in different departments is done with inconsistent definitions, leading to different business rules. This can result in duplicate data entry and make it difficult to integrate data from different systems.
• No data lineage information resulting in limited transparency of dataflows. Data lineage is the ability to track the origin and flow of data through an organization. This information is essential for understanding how data is used and for ensuring compliance with regulations.
• Roles and responsibilities for data are not effectively set, ownership of data is not clearly established within the organisation, leading to unclear accountabilities for data sets. This can make it difficult to manage data and to ensure that it is used responsibly.
• Data quality issues are resolved reactive and manually, without investigating the root cause for a data quality issue. This can lead to recurring data quality problems.
• There is no ongoing monitoring of whether data is fit for purpose for your organisation or whether the state of data is improving over time. This can make it difficult to ensure that data is meeting the needs of the organization.

News items about companies without data governance:

• Equifax data breach: A failure of data governance? (The Guardian, 2017)
• Facebook-Cambridge Analytica scandal: A cautionary tale for data governance (Forbes, 2018)
• Marriott Hacking Exposes Data of Up to 500 Million Guests (The New York Times, 2018)
• Capital One Data Breach Compromises Data of Over 100 Million (The New York Times, 2019)
  

These news items highlight the risks of not having effective data governance in place. Companies without data governance are more likely to experience data breaches, compliance violations, and other problems.

Conclusion

Effective data governance is essential for organizations that want to manage their data as a strategic asset. Data governance can help organizations to improve regulatory compliance, ensure consistent data definitions, solve data analytics and reporting issues, and reduce costs.