Auditing in Data Governance: Ensuring Integrity and Accountability

Auditing is a cornerstone of a robust data governance framework. It provides organisations with the ability to systematically review, verify, and improve their data management practices while maintaining accountability. A well-executed audit ensures compliance with legal, regulatory, and organisational standards and mitigates risks associated with data breaches or mismanagement.

Why Auditing is Essential

Auditing validates the implementation of data governance policies and highlights gaps in processes, such as access control failures or inconsistent data classification. It also fosters trust by demonstrating transparency and a commitment to data stewardship.

What to target in an Audit?

Whilst it is tempting to go down the route of ISO 27701 – Privacy Information Management or ISO 27001 – Information Security Management, I have found using CMMI’s Data Capability Maturity Model to advance the needs of data governance program sufficiently enough to get the organisation thinking about their stance on data. A preview of their model can be found online here.

Key Components of a Data Audit

1. Access Logs: Regularly review logs to ensure that only authorised personnel accessed sensitive data.
2. Data Quality Checks: Evaluate datasets for accuracy, completeness, and timeliness using tools like Talend or Power BI.
3. Compliance Metrics: Verify alignment with regulatory frameworks, such as GDPR or HIPAA.
4. Change Management: Review records of changes to datasets or systems, ensuring they follow approval workflows.

Where possible, my recommendation is to automate reporting. This allows you to work on the key problems quickly. The first 3 audits should must be done manually, so you know what kinds of questions to ask, what behaviours to look out for and all the various anomalies. And once your reports are automated, you should work on reviewing them on an annual basis by doing a 10% sample from each quarter to validate your findings. Because once people know rules, it becomes easier to “manipulate” the game.

Conducting an Effective Audit

1. Preparation: Define the scope, goals, and KPIs for the audit. Ensure access to necessary tools and personnel.
2. Execution: Use a mix of automated tools and manual reviews to identify discrepancies.
3. Reporting: Document findings in detail, including corrective actions and timelines for implementation.

In Closing

Auditing isn’t just a compliance exercise—it’s a strategic enabler for long-term data integrity. It empowers organisations to manage their data assets with confidence and foresight.

For more details on the blueprint behind implementing a good data governance program – click here!

If you’d like assistance or advice with your Data Governance implementation, please feel free to drop me an email here and I will endeavour to get back to you as soon as possible!