A tailored course, built for your situation
Pragmatic Customer Data Platform Programs for Audit Teams
Implementation-grade strategies for audit-ready data governance and compliance
$199 one-time
24-hour access provisioning
30-day money-back guarantee
Hand-built implementation playbook
12 modules. 12 chapters per module. 144 chapters total.
12 modules, each with 12 chapters (144 chapters total), text-based, plus downloadable templates and a hand-built implementation playbook delivered alongside course access.
Audit teams face increasing pressure to validate data integrity across fragmented systems without clear frameworks or ownership.
The situation this course is for
Customer data lives in siloed platforms with inconsistent governance, making audits reactive, time-intensive, and prone to gaps. Traditional approaches lack integration with modern data architectures, leaving compliance teams playing catch-up.
Who this is for
Business or technology professionals in audit, compliance, risk, or governance roles who need to establish control within customer data ecosystems.
Who this is not for
This is not for software developers building CDPs, nor for marketers using customer data. It’s for audit and assurance professionals needing to govern, not operate, the platform.
What you walk away with
- Map customer data platforms to audit requirements and control frameworks
- Design audit-specific access models within CDP architectures
- Implement data lineage and retention controls aligned with compliance cycles
- Build repeatable assurance workflows for ongoing CDP oversight
- Translate technical CDP configurations into audit evidence packages
The 12 modules (with all 144 chapters)
Module 1. Audit in the Age of Data Platforms
Understanding the evolution of audit roles in data-driven organizations.
12 chapters in this module
- From periodic review to continuous assurance
- The rise of platform-based compliance
- Audit scope in multi-system CDP environments
- Defining control boundaries across teams
- Compliance as a design requirement
- Regulatory expectations for customer data
- How CDPs change data provenance
- Common audit risks in customer data
- The shift from reactive to proactive assurance
- Building credibility with engineering teams
- Aligning with privacy frameworks
- Setting expectations for cross-functional collaboration
Module 2. Customer Data Platform Fundamentals
Core components and data flows in modern CDPs.
12 chapters in this module
- What defines a customer data platform
- Key vendors and architectural patterns
- Data ingestion and identity resolution
- Consent and preference management
- Profile unification mechanics
- Event stream processing basics
- Data activation channels
- Storage layers and indexing
- APIs and integration points
- Metadata management in CDPs
- Data freshness and latency
- Common data models in customer platforms
Module 3. Governance by Design
Embedding audit principles into CDP architecture.
12 chapters in this module
- Shifting left on compliance
- Designing for auditability from day one
- Ownership models for data domains
- Policy as code in data platforms
- Automated control assertions
- Versioning data contracts
- Change management for CDPs
- Audit trails for configuration changes
- Access review automation
- Data classification frameworks
- Handling shadow CDPs
- Cross-platform governance alignment
Module 4. Data Lineage and Provenance
Tracing data from source to insight for audit validation.
12 chapters in this module
- Why lineage matters for compliance
- Types of data lineage: structural and operational
- Automated vs manual lineage tracking
- Mapping data transformations
- Identity stitching transparency
- Third-party data onboarding
- Consent tracking across systems
- Data expiration and deletion workflows
- Reconstructing historical states
- Lineage for regulatory reporting
- Validating ETL accuracy
- Documenting data movement for auditors
Module 5. Access Control and Permissions
Securing data access while enabling audit oversight.
12 chapters in this module
- Role-based access in CDPs
- Attribute-based access control
- Segregation of duties in data workflows
- Audit-only access design
- Time-bound permissions
- Just-in-time access models
- Monitoring for privilege creep
- Access certification cycles
- Logging access for review
- Handling emergency access
- Third-party vendor access
- Access review automation
Module 6. Data Retention and Deletion
Managing lifecycle compliance in customer data systems.
12 chapters in this module
- Regulatory retention periods
- Data minimization in practice
- Scheduled deletion workflows
- Right to be forgotten execution
- Verification of deletion
- Archival vs deletion
- Legal hold processes
- Cross-system data mapping
- Data retention in backups
- Reporting on deletion status
- Audit evidence for deletion
- Handling incomplete deletions
Module 7. Consent and Preference Management
Validating customer consent across platforms.
12 chapters in this module
- Consent as a compliance cornerstone
- Consent capture methods
- Storing consent records
- Mapping consent to data usage
- Preference synchronization
- Withdrawal workflows
- Consent for minors
- Jurisdictional variations
- Audit testing of consent
- Consent reporting
- Handling implied consent
- Consent fraud detection
Module 8. Cross-System Data Integrity
Ensuring consistency across CDPs and downstream systems.
12 chapters in this module
- Data synchronization challenges
- Validating data replication
- Detecting data drift
- Reconciliation methods
- Data quality monitoring
- Error handling in pipelines
- Data accuracy benchmarks
- Source of truth designation
- Handling conflicting data
- Data validation at scale
- Automated anomaly detection
- Reporting data integrity issues
Module 9. Audit Evidence Automation
Generating consistent, real-time audit artifacts.
12 chapters in this module
- From manual collection to automated evidence
- Defining evidence requirements
- Automated log extraction
- Evidence packaging formats
- Timestamping and immutability
- Evidence retention policies
- Chain of custody documentation
- Integrating with GRC tools
- Evidence for external auditors
- Sampling strategies
- Automated anomaly flagging
- Evidence validation workflows
Module 10. Risk-Based Audit Planning
Prioritizing audit focus based on data risk.
12 chapters in this module
- Risk assessment frameworks
- Identifying high-risk data flows
- Impact vs likelihood scoring
- Third-party risk in CDPs
- Vendor data handling review
- Data sensitivity classification
- Threat modeling for CDPs
- Audit frequency by risk tier
- Resource allocation strategies
- Risk-based sampling
- Reporting risk exposure
- Updating risk profiles
Module 11. Cross-Functional Collaboration
Working effectively with engineering, legal, and product teams.
12 chapters in this module
- Speaking the language of engineers
- Legal and compliance alignment
- Product team engagement
- Facilitating joint design sessions
- Conflict resolution strategies
- Building trust across functions
- Audit influence without authority
- Translating technical details
- Creating shared goals
- Feedback loops for improvement
- Managing expectations
- Documenting joint decisions
Module 12. Building the Audit-Ready CDP Program
Integrating all components into a sustainable program.
12 chapters in this module
- Defining program objectives
- Stakeholder alignment
- Roadmap development
- Measuring program success
- Continuous improvement cycles
- Scaling audit practices
- Training and enablement
- Knowledge transfer strategies
- Program documentation
- External validation readiness
- Lessons from early adopters
- Next-generation audit evolution
How this maps to your situation
- New CDP rollout with audit concerns
- Post-breach compliance review
- Regulatory audit preparation
- Cross-functional data governance initiative
Before vs. after
Before
Manual, reactive audits with fragmented evidence and limited visibility into data systems.
After
Proactive, structured oversight with automated evidence, clear ownership, and audit-by-design principles embedded in the CDP.
What's included with your purchase
- 12 modules with 12 chapters each (144 chapters)
- Downloadable templates and worked examples for every module
- Hand-built implementation playbook delivered alongside course access
- 30-day money-back guarantee
Delivery and format
- Course and learning environment access provisioned within 24 hours of purchase
- Hand-built implementation playbook delivered alongside course access
Format: Text-based modules and chapters in the Art of Service learning environment, plus downloadable templates and worked examples for every chapter, plus the hand-built implementation playbook delivered alongside course access.
Time investment: Approximately 45, 60 hours total, designed for self-paced learning with implementation milestones.
If nothing changes
Without structured governance, audit teams face increasing complexity, longer cycles, and higher risk of non-compliance as customer data platforms grow in scope and scale.
How this compares to the alternatives
Unlike generic data governance courses, this program focuses exclusively on audit-specific controls, evidence generation, and compliance integration within customer data platforms, delivering actionable, implementation-grade knowledge.
Frequently asked
Who is this course designed for?
Audit, compliance, risk, and governance professionals working with or overseeing customer data platforms.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Is prior technical experience required?
No, concepts are explained in accessible language with practical examples tailored to audit and compliance contexts.
$199 one-time. Approximately 45, 60 hours total, designed for self-paced learning with implementation milestones..
Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.
30-day money-back guarantee·
144 chapters·
Hand-built playbook included·
Account access within 24 hours