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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 - Control Objectives for Information Technologies

Workspaces

Data Centers
IT departments
Corporate offices

Occupations

Data Governance Officer
Chief Data Officer
Data Steward
IT Manager
Compliance Officer
1
Is the data governance framework compliant with COBIT standards?
2
What is the current data quality score based on defined metrics?
Min: 0
Target: 80
Max: 100
3
Are the roles and responsibilities for data stewardship clearly defined?
4
What actions are being taken to improve data governance?
5
Is the data retention policy in compliance with regulatory requirements?
6
What data classification standards are being applied?
7
When was the last review of the data lifecycle processes conducted?
8
What is the current data deletion rate as a percentage?
Min: 0
Target: 90
Max: 100
9
Are metadata management standards established and documented?
10
Describe the current state of the metadata catalog.
11
What is the metadata compliance score based on audits?
Min: 0
Target: 85
Max: 100
12
How would you rate the quality of the metadata?
13
Are access control measures implemented and effective?
14
Is data encryption implemented for sensitive information?
15
What is the average incident response time in hours?
Min: 0
Target: 2
Max: 24
16
Describe any recent security incidents affecting data security.
17
Are the architecture design principles documented and followed?
18
Are data flow diagrams available and up-to-date?
19
What is the current score for system integration effectiveness?
Min: 0
Target: 75
Max: 100
20
What future improvements are planned for the data architecture?

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 of COBIT Data Governance Audit Checklist

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