A tailored course, built for your situation
Sources and specific examples on hand when peers push back
Build defensible positions in data validation work that hold up under technical scrutiny
$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.
Who this is for
Mid-senior IC data quality practitioner in regulated enterprise environments who owns test validation and must justify methodological choices under peer scrutiny
Who this is not for
Junior testers who follow checklists without ownership, or managers seeking team-wide compliance frameworks
What you walk away with
- Identify the three core validation patterns used in high-assurance BI pipelines and cite where each applies best
- Map test design decisions to source system behavior with concrete lineage examples
- Anticipate technical pushback using a structured rebuttal library tied to common ETL patterns
- Document reasoning trails that survive handoffs and audit cycles
- Turn ad hoc peer questions into reusable defensible templates for future validations
The 12 modules (with all 144 chapters)
Module 1. Pattern One: Schema Drift Detection
Learn how to distinguish expected from risky schema changes using versioned source mappings and historical drift logs across 6 real finance-sector pipelines.
12 chapters in this module
- Schema drift vs. data drift
- Capture method: diff logs
- Golden copy thresholds
- Source: DB2 to DataStage
- Case: currency field type shift
- Alerting on silent truncation
- Documentation timing
- Peer challenge: 'Why flag this?'
- Response template library
- Version control integration
- Frequency benchmarks
- Handoff to DevOps
Module 2. Pattern Two: Null Value Propagation
Trace null handling across transformations and build reasoning for acceptance or rejection based on business rule intent and SLA requirements.
12 chapters in this module
- Nulls in source systems
- Intent: missing vs. unknown
- Transformation layer rules
- Impact on KPIs
- Case: sales region nulls
- Upstream fix feasibility
- Documentation standard
- Challenge: 'We always allow nulls'
- Response with precedent
- Template: escalation path
- Benchmark: null tolerance
- Cross-team alignment
Module 3. Pattern Three: Business Rule Enforcement
Anchor test cases to documented business logic and regulatory references, making validation decisions auditable and consistent.
12 chapters in this module
- Rule source identification
- Regulatory tie-ins
- Mapping to test scripts
- Case: tax calculation logic
- Challenge: 'That rule changed'
- Versioned rule tracking
- Change approval trail
- Response: 'Here's the current rule'
- Template: rule validation log
- Integration with Jira
- Audit readiness
- Stakeholder alignment
Module 4. Pattern Four: Data Type Mismatches
Justify validation failures due to type mismatches with system specs, migration histories, and downstream impact analysis.
12 chapters in this module
- Source system data types
- Target system expectations
- Case: integer to decimal
- Impact on aggregations
- Migration history review
- Challenge: 'It worked before'
- Response: behavior change
- Template: compatibility matrix
- Type safety benchmarks
- Dev team collaboration
- Documentation standard
- Escalation criteria
Module 5. Pattern Five: Duplicate Record Handling
Define acceptable duplication thresholds and defend filtering logic using system load patterns and business context.
12 chapters in this module
- Expected duplicates
- Load batch timing
- Case: retry mechanisms
- Business tolerance
- Challenge: 'We need all records'
- Response: accuracy impact
- Template: dedup logic doc
- SLA alignment
- Metrics: duplication rate
- Downstream effects
- Review cycle timing
- Handoff documentation
Module 6. Pattern Six: Timestamp Precision Issues
Defend time-based validation rules using system clock sync logs, timezone handling specs, and query execution timing evidence.
12 chapters in this module
- Clock sync standards
- Source system time zones
- ETL transformation rules
- Case: 3ms delay issue
- Challenge: 'It’s close enough'
- Response: SLA breach risk
- Template: time drift log
- Precision benchmarks
- System logs review
- Stakeholder alignment
- Documentation standard
- Escalation path
Module 7. Pattern Seven: Referential Integrity Breaks
Justify blocking pipeline runs when FK constraints fail, using dependency maps and downstream model integrity risks.
12 chapters in this module
- Parent-child table mapping
- Dependency chain analysis
- Case: customer ID missing
- Challenge: 'Run it anyway'
- Response: model corruption
- Template: dependency tree
- Risk scoring
- Dev team coordination
- Documentation standard
- Escalation criteria
- Review frequency
- Audit trail
Module 8. Pattern Eight: Aggregate Value Discrepancies
Explain variances in summarised metrics using source-level traceability and transformation logic walkthroughs.
12 chapters in this module
- Source record count
- Transformation math
- Case: sum mismatch
- Rounding rule impact
- Challenge: 'It’s within range'
- Response: trend integrity
- Template: variance log
- Tolerance thresholds
- Lineage mapping
- Stakeholder review
- Documentation standard
- Escalation path
Module 9. Pattern Nine: Masked Data Validation
Verify masked outputs without accessing raw data using pattern consistency checks and rule-based verification.
12 chapters in this module
- Masking rule definition
- Case: SSN obfuscation
- Pattern consistency
- Challenge: 'Can't validate blind'
- Response: rule adherence
- Template: masking log
- Rule enforcement check
- Audit readiness
- Dev team alignment
- Documentation standard
- Review cycle
- Escalation
Module 10. Pattern Ten: Outlier Detection Logic
Defend outlier flagging decisions using statistical benchmarks and domain-specific thresholds documented in test design.
12 chapters in this module
- Statistical baseline
- Domain thresholds
- Case: sales spike
- Legitimate vs. error
- Challenge: 'Don’t filter real data'
- Response: anomaly process
- Template: outlier log
- Review workflow
- Documentation standard
- Stakeholder input
- Escalation criteria
- Handoff process
Module 11. Pattern Eleven: Pipeline Restart Validity
Assess whether restarted batches introduce duplication or gaps, and justify revalidation scope based on system logs.
12 chapters in this module
- Restart mechanism
- Batch ID continuity
- Case: duplicate inserts
- Challenge: 'It’s just a restart'
- Response: data integrity
- Template: restart log
- Gap detection method
- Documentation standard
- Dev team coordination
- Review timing
- Escalation path
- Audit trail
Module 12. Pattern Twelve: Metadata Consistency
Ensure field descriptions, units, and sources align across systems using automated consistency checks and documentation trails.
12 chapters in this module
- Metadata source
- Field description sync
- Case: unit mismatch
- Challenge: 'Everyone knows what it means'
- Response: clarity risk
- Template: metadata log
- Consistency benchmark
- Documentation standard
- Review cycle
- Stakeholder alignment
- Escalation criteria
- Handoff
How this maps to your situation
- When a peer questions a test failure
- During audit preparation cycles
- When onboarding new team members
- Before signing off on pipeline changes
Before vs. after
Before
Peer challenges to data validation decisions required reactive justification and sometimes reversal due to lack of documented reasoning.
After
Every validation decision is backed by source references, precedent, and structured logic, making pushback a routine walkthrough, not a risk.
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 3 hours per module, designed for integration into weekly validation planning cycles.
How this compares to the alternatives
Generic QA courses teach test case writing; this course teaches how to defend high-stakes validation decisions with precision and authority, using real patterns from regulated data pipelines.
Frequently asked
Who is this course for?
Mid-to-senior level ETL and BI QA analysts who own validation decisions and must defend them under technical scrutiny.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Does this course include templates?
Yes, each module includes downloadable templates and real-world worked examples you can adapt immediately.
$199 one-time. Approximately 3 hours per module, designed for integration into weekly validation planning cycles..
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