ISACA Pittsburgh will be hosting a 2 day virtual training event.
October 14th and October 15th from 8:30 AM - 5:00 PM EST both days.
- How to Perform a Data Governance Audit - with AI Risk Considerations
Detailed information about the class:
Seminar Objective
• Determine whether an overall effective data governance program has been implemented.
• Determine whether an effective organizational structure has been established.
• Determine whether effective data quality controls have been established to ensure accuracy, completion, and timeliness.
• Determine whether effective issue escalation and resolution processes have been established.
• Determine whether the Key Data Elements have been properly identified.
• Understand the recent AI trends which impact the Data Governance program.
• Provide alternative approaches for building out a Data Governance program.
• Establish effective audit test procedures to evaluate a Data Governance program.
Seminar Length
Two days (7 ½ -hour presentation time per day plus 1-hour lunch and four 10-minute breaks per day)
Who Should Attend
This seminar is designed for senior IT Auditors, Security and GRC personnel.
Continuing Professional Education Credits
All attendees are eligible to receive 15 hours of continuing professional education (CPE) credits issued by the Pittsburgh Chapter.
Seminar Outline The following topics will be discussed:
Introduction to Data Governance Concepts
- What is Data Governance?
- Difference between Data Governance and Data Management
Data Governance Structure
Key Pillars of Data Governance
- Data Governance Policies, Standards, Framework & Procedures
- Data Ownership
- Critical & Key Data Elements (CDE/KDE) Standards and Controls
- Data Quality Management
- Data Issue Management and Resolution
- Change Management
- Data Lineage
- Metadata Management
- Authoritative Data Sources
- System of Record
- Golden Data Sources
- Reference Data
Dependent project initiatives from Information Security
- Data Classification Implementation
- Data Privacy
- Data Security
- Data Retention and Destruction
AI Impacts on the Data Governance Program
- Traceability of data
- Additional Confidential, Integrity and Availability risks based on AI Models and Agents
Building the Data Governance Program
- Governance Initiatives
- Operational Rollouts
- Establishing Policy, Standards and Framework
- Establishing a Roadmap
- Data Governance Committee
- Data Governance Charter
- Federal Laws which require organizations to establish Data Governance Initiatives
- Data Governance Challenges
- Determining the current state of your Data Governance program
- Typical Data Governance Project Life Cycle
- Establishing RACI Matrix for the Data Governance Project
- Minimum Expectation for a Data Governance Implementation
Conducting a Data Governance Audit
- Determine whether an overall effective data governance program has been implemented
- Determine whether an effective organizational structure has been established
- Determine whether the scope of the Data Governance Initiative has been adequately established
- Determine whether the Critical/Key Data Elements have been properly identified
- Determine whether effective data quality controls have been established to ensure accuracy, completion, and timeliness
- Determine whether effective issue escalation and resolution occurs
- Determine whether effective software development and change management controls have been established for Data Quality Rules
- Determine whether effective data lineage processes have been established
- Determine whether Authoritative Data Sources have been identified
- Determine whether effective data metrics and management reporting exists
A case study will be presented during this seminar which will provide the attendee the understanding of how to evaluate the implementation of a Data Governance structure