A tailored course, built for your situation
Deeper command of data lineage frameworks in Fabric environments
Master the underlying architecture patterns, metadata flows, and dependency mappings that define reliable data governance in modern data stacks
$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
Senior data engineer working in enterprise cloud environments with Oracle, Microsoft Fabric, and Power BI, focused on delivering governed, traceable data pipelines at scale
Who this is not for
Entry-level analysts, dashboard developers without backend integration tasks, or professionals working exclusively in pre-built SaaS analytics tools without access to metadata layers
What you walk away with
- Confidence to define end-to-end lineage standards without escalation
- Reproducible templates for metadata tagging and dependency mapping
- Clear articulation of Fabric-native integration points with TDM and Power BI
- Ability to anticipate audit questions and embed answers in pipeline design
- Faster resolution of cross-team disputes over data ownership and transformation logic
The 12 modules (with all 144 chapters)
Module 1. Fabric metadata architecture
Understand the hierarchical structure of metadata stores in Fabric, including workspace-level governance, item-level tagging, and cross-environment inheritance patterns used in enterprise deployments.
12 chapters in this module
- Metadata store hierarchy
- Workspace vs item scope
- Inheritance rules
- Tagging standards
- Ownership models
- Lifecycle states
- Export formats
- Versioning logic
- Schema evolution
- Dependency tracking
- Audit trail structure
- Access control layers
Module 2. Data flow tracing in OneLake
Map how data moves across domains in OneLake, identifying implicit and explicit links between notebooks, pipelines, and semantic models using native observability signals.
12 chapters in this module
- OneLake domain boundaries
- Implicit vs explicit links
- Notebook to pipeline trace
- Semantic model sources
- Refresh dependency chains
- Dataflow lineage paths
- Cross-workspace references
- Short-cut tracking
- Delta format markers
- Schema drift detection
- Load sequence inference
- Orphaned object handling
Module 3. End-to-end lineage representation
Build comprehensive lineage diagrams that integrate source system origins, transformation logic, and consumption touchpoints using standardized notation and tool-agnostic principles.
12 chapters in this module
- Origin identification
- ETL logic mapping
- Column-level tracing
- Transformation rules
- Join path tracking
- Filter propagation
- Calculated measures
- Aggregation traceability
- Consumption layer links
- BI report connections
- Dashboard dependency trees
- Version-to-version continuity
Module 4. TDM integration patterns
Design test data management workflows that preserve referential integrity and masking rules while maintaining lineage accuracy across non-production environments.
12 chapters in this module
- Masking impact on lineage
- Subset extraction rules
- Referential integrity
- Environment synchronization
- Data refresh triggers
- Test scenario tagging
- Anonymization logs
- Source deviation tracking
- Validation checkpoints
- Pipeline branching
- Version locking
- Approval gate alignment
Module 5. Power BI semantic model linkage
Trace relationships between Power BI datasets, DAX expressions, and upstream Fabric entities, ensuring model logic remains auditable and version-controlled.
12 chapters in this module
- Dataset source mapping
- DAX expression tracing
- Measure logic flow
- Relationship lineage
- Hierarchical path tracking
- Calculated columns
- Time intelligence links
- Parameter propagation
- Role-level filtering
- Report interaction effects
- Query folding visibility
- Performance tuning markers
Module 6. Cross-system dependency mapping
Identify and document dependencies that span Fabric, external databases, APIs, and legacy ETL tools using unified mapping conventions and ownership assignment rules.
12 chapters in this module
- External database links
- API endpoint tracing
- Legacy ETL integration
- Hybrid environment mapping
- Ownership assignment
- SLA boundary definition
- Change notification paths
- Breakage risk factors
- Recovery sequence logic
- Fallback mechanism tracking
- Credential dependency
- Rate limit impacts
Module 7. Metadata tagging standards
Implement consistent, searchable tagging practices for data classification, sensitivity, ownership, and business context that align with governance frameworks.
12 chapters in this module
- Classification tiers
- Sensitivity labeling
- Business owner tagging
- System owner assignment
- Regulatory category tags
- Retention period markers
- Usage restriction flags
- PII detection integration
- GDPR alignment
- Data domain categorization
- Custom property extension
- Tag validation rules
Module 8. Artefact standardization
Develop repeatable templates for lineage documentation, data dictionaries, and audit readiness packages that reduce variance across teams and projects.
12 chapters in this module
- Lineage doc templates
- Data dictionary structure
- Audit package contents
- Standard section ordering
- Version header format
- Reviewer checklist
- Cross-reference indexing
- Change log conventions
- Approval signature blocks
- Tool export harmonization
- Naming consistency
- Glossary integration
Module 9. Ambiguity pre-resolution
Anticipate common points of confusion in data provenance and embed resolution logic directly into pipeline design and metadata publication.
12 chapters in this module
- Common ambiguity sources
- Default rule setting
- Null handling transparency
- Transformation logic annotation
- Assumption documentation
- Fallback selection
- Data quality rule embedding
- Error path mapping
- User expectation alignment
- Stakeholder question forecasting
- Dispute prevention
- Preemptive clarification
Module 10. Governance decision fluency
Build confidence in making or challenging architecture decisions by mastering the rationale behind common design patterns and trade-offs.
12 chapters in this module
- Single source of truth
- Staging layer necessity
- Data vault applicability
- Star schema timing
- Slowly changing dimensions
- Surrogate key logic
- Incremental load design
- Watermark management
- Backfill strategy
- Cost-performance balance
- Refresh frequency impact
- Latency tolerance
Module 11. Source-backed reasoning
Support every design choice with documented references to platform behavior, official documentation, or implementation benchmarks from comparable environments.
12 chapters in this module
- Platform behavior logs
- Official doc citations
- Benchmark comparisons
- Internal case examples
- Peer validation
- Tooling limitations
- Performance data
- Error rate evidence
- Adoption patterns
- Change request history
- Architecture review minutes
- Escalation resolution records
Module 12. Implementation playbook integration
Adapt course patterns into your operational workflow using the hand-built playbook tailored to your environment’s common scenarios and constraints.
12 chapters in this module
- Playbook navigation
- Scenario matching
- Template customization
- Team adoption planning
- Review cycle alignment
- Tool integration steps
- Stakeholder communication
- Feedback loop setup
- Continuous improvement
- Version update tracking
- Knowledge transfer
- Success measurement
How this maps to your situation
- When onboarding a new data domain
- Before initiating a major pipeline redesign
- During preparation for internal audit
- When resolving cross-team ownership disputes
Before vs. after
Before
Lineage documentation is assembled reactively, with inconsistent formats and gaps in transformation logic tracing.
After
Lineage is engineered proactively into pipeline design, with standardized, source-backed artefacts that withstand scrutiny.
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 3-4 hours per module, recommended over six weeks with applied practice between modules.
How this compares to the alternatives
Unlike generic data governance courses, this program focuses exclusively on the architectural nuances of Microsoft Fabric and its intersection with TDM and Power BI, providing field-tested decision frameworks rather than theoretical models.
Frequently asked
Is this course specific to Microsoft Fabric?
Yes, all examples, templates, and decision frameworks are built around Fabric's architecture, metadata model, and integration patterns.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Does the course cover Power BI lineage in depth?
Yes, Module 5 focuses entirely on tracing Power BI semantic models back to upstream Fabric entities and transformation logic.
$199 one-time. Approximately 3-4 hours per module, recommended over six weeks with applied practice between modules..
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