COBIT Data Governance Audit Checklist

A comprehensive checklist for auditing data governance practices based on the COBIT framework, covering key areas such as data quality management, data security and privacy, metadata management, data lifecycle management, and data architecture.

COBIT Data Governance Audit Checklist
by: audit-now
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About This Checklist

The COBIT Data Governance Audit Checklist is a critical tool for organizations aiming to enhance their data management and governance practices within the COBIT framework. This comprehensive checklist enables data governance professionals, IT leaders, and auditors to systematically evaluate and improve their organization's approach to data quality, security, and compliance. By addressing key data governance domains outlined in COBIT, this checklist helps organizations build a robust data governance framework that ensures data integrity, enhances decision-making, and maximizes the value of data assets. It serves as a guide for implementing effective data policies, standards, and procedures that align with business objectives and regulatory requirements.

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Industry

Information Technology

Standard

COBIT

Workspaces

Data management centers
IT departments
Corporate offices

Occupations

Data Governance Officer
Chief Data Officer
Data Steward
IT Manager
Compliance Officer

Data Governance Processes Audit

(0 / 4)

1
What actions are being taken to improve data governance?

Provide details of improvement actions.

Identifies ongoing initiatives for enhancing data governance.
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2
Are the roles and responsibilities for data stewardship clearly defined?

Select true if roles are defined, false otherwise.

Clarifies accountability and ensures effective data governance.
3
What is the current data quality score based on defined metrics?

Enter data quality score out of 100.

Helps to quantify the effectiveness of data governance processes.
Min: 0
Target: 80
Max: 100
4
Is the data governance framework compliant with COBIT standards?

Select compliance status.

Ensures alignment with industry best practices and regulatory requirements.
5
What is the current data deletion rate as a percentage?

Enter the data deletion rate percentage.

Measures the effectiveness of data lifecycle management practices.
Min: 0
Target: 90
Max: 100
6
When was the last review of the data lifecycle processes conducted?

Enter the date of the last review.

Tracks the frequency of reviews to ensure the processes are current.
7
What data classification standards are being applied?

Specify the data classification standards applied.

Identifies how data is categorized to manage its lifecycle effectively.
8
Is the data retention policy in compliance with regulatory requirements?

Select compliance status.

Ensures that data is retained or disposed of according to legal and compliance obligations.
9
How would you rate the quality of the metadata?

Select the quality assessment rating.

Assesses the reliability and completeness of metadata for decision-making.
10
What is the metadata compliance score based on audits?

Enter the metadata compliance score out of 100.

Quantifies adherence to established metadata standards.
Min: 0
Target: 85
Max: 100
11
Describe the current state of the metadata catalog.

Provide a detailed description of the metadata catalog.

Provides insight into the completeness and usability of the metadata catalog.
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12
Are metadata management standards established and documented?

Select true if standards are established, false otherwise.

Ensures consistency and quality in metadata management practices.
13
Describe any recent security incidents affecting data security.

Provide details of any recent security incidents.

Identifies vulnerabilities and areas for improvement in security practices.
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14
What is the average incident response time in hours?

Enter the average incident response time in hours.

Measures the efficiency of the incident response plan.
Min: 0
Target: 2
Max: 24
15
Is data encryption implemented for sensitive information?

Select true if data encryption is implemented, false otherwise.

Ensures that sensitive data is protected during storage and transmission.
16
Are access control measures implemented and effective?

Select access control effectiveness status.

Verifies that only authorized personnel can access sensitive data.
17
What future improvements are planned for the data architecture?

Provide details on planned architecture improvements.

Identifies strategic enhancements for better data management and accessibility.
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18
What is the current score for system integration effectiveness?

Enter the system integration score out of 100.

Quantifies how well different systems work together within the architecture.
Min: 0
Target: 75
Max: 100
19
Are data flow diagrams available and up-to-date?

Specify the availability status of data flow diagrams.

Verifies that data flows within systems are clearly mapped and understood.
20
Are the architecture design principles documented and followed?

Select if the principles are documented and followed.

Ensures that data architecture aligns with organizational goals and standards.

FAQs

This checklist covers areas such as data quality management, data security and privacy, metadata management, data lifecycle management, and data architecture, all aligned with COBIT principles for IT governance and management.

By providing a structured approach to evaluating data governance processes, the checklist helps identify gaps in data management practices, establish data quality metrics, and implement data quality improvement initiatives.

The audit should involve data governance officers, chief data officers, data stewards, IT managers, compliance officers, and key stakeholders from various business units that rely on data for decision-making.

Organizations should conduct this audit annually, with more frequent assessments recommended for critical data assets or after significant changes in data management practices or regulatory requirements.

Yes, this checklist includes sections specifically designed to assess compliance with data protection regulations such as GDPR, CCPA, and industry-specific data standards, helping organizations maintain regulatory compliance.

Benefits

Ensures comprehensive coverage of data governance principles and practices

Facilitates alignment of data management with business goals and regulatory compliance

Improves data quality, reliability, and accessibility across the organization

Enhances data security and privacy measures

Supports better decision-making through improved data management and utilization