A tailored course, built for your situation
Repeatable data modelling patterns that compound across projects
Build a self-reinforcing library of trusted, reusable specs that accelerate every new pipeline
$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-level data engineer analysts working in cloud data platforms who deliver DBT-driven pipelines and want to increase velocity without sacrificing governance or clarity
Who this is not for
Engineers who only run ad-hoc queries or maintain legacy ETL without ownership of model semantics; practitioners not using DBT or modular transformation layers
What you walk away with
- A personal library of 8+ battle-tested data model patterns you can reuse across clients or business units
- A stakeholder-backed template for scoping dimensional models that reduces revision cycles
- A standardised naming and documentation convention adopted across your recent DBT pipelines
- A framework to evaluate which model components can be abstracted for future reuse
- A tracked portfolio of compoundable specs linked to actual deliveries
The 12 modules (with all 144 chapters)
Module 1. Why compounding beats rework in data modelling
Understand how top practitioners convert individual deliverables into assets that reduce future effort while increasing accuracy and trust.
12 chapters in this module
- The cost of one-off modelling
- Where rework hides in DBT flows
- Patterns vs templates: key distinction
- How compounding starts small
- Real-world example: sales funnel model
- Tracking model decay over time
- The 30-minute reuse test
- When to standardise vs customise
- Ownership of semantics
- Downstream drift risks
- Snowflake schema conventions
- DBT project hygiene
Module 2. Identifying compoundable components
Learn to spot which parts of your current work can be turned into reusable, trustworthy building blocks.
12 chapters in this module
- Atomicity of dimension tables
- Shared grain detection
- Surrogate key portability
- Cutoff logic across time zones
- Currency conversion patterns
- Hierarchy handling norms
- Soft delete strategies
- Effective dating templates
- Null handling standards
- Role-based access patterns
- Audit trail requirements
- Documentation completeness
Module 3. Designing for reuse, not just completion
Shift from delivering isolated models to creating components that retain value across engagements.
12 chapters in this module
- Naming beyond team slang
- Versioning model interfaces
- Input contract specifications
- Output SLA definitions
- Modular CTE structuring
- Fact table binding rules
- Cross-model dependency map
- Change propagation cost
- Backfill resilience design
- Testing boundary assumptions
- Documentation triggers
- Handoff checklist
Module 4. Building a personal IP library
Create your own repository of trusted components that accelerates future work.
12 chapters in this module
- Selecting first three models
- Folder structure logic
- README conventions
- Version control tagging
- Use case tagging system
- Ownership declaration
- Peer validation method
- Internal sharing protocol
- Feedback collection loop
- Update frequency rules
- Retirement criteria
- Cross-project audit trail
Module 5. Standardising transformation logic
Turn ad-hoc SQL into consistent, reusable transformations that scale across pipelines.
12 chapters in this module
- Date spine reuse
- Time window aggregation
- Sessionisation thresholds
- Revenue allocation rules
- User stitching logic
- Device graph patterns
- Attribution window settings
- Null imputation rules
- Currency normalisation
- Time zone conversion
- Hierarchy rollup method
- Data quality thresholds
Module 6. Documenting for compound growth
Write documentation that makes your patterns discoverable and trustworthy to others.
12 chapters in this module
- Purpose clarity
- Assumption logging
- Data origin chain
- Business rule source
- Stakeholder sign-off
- Performance benchmarks
- Known limitations
- Version migration path
- Test coverage summary
- Usage examples
- Ownership contact
- Review cycle date
Module 7. Tracking pattern adoption and impact
Measure how your reusable assets reduce delivery time and increase trust.
12 chapters in this module
- First-use validation
- Cycle time tracking
- Rework reduction
- Peer adoption count
- Downstream dependency count
- Change propagation speed
- QA failure reduction
- Documentation completeness score
- Model accuracy stability
- Business stakeholder feedback
- Support request volume
- Onboarding time saved
Module 8. Scaling reuse across teams
Expand your personal system into a shared standard without losing agility.
12 chapters in this module
- Internal open sourcing
- Approval gate process
- Cross-team review cadence
- Governance lightweight model
- Conflict resolution path
- Naming standards alignment
- Backward compatibility
- Deprecation notice
- Migration support period
- Version support tiers
- Security review checklist
- Data classification tagging
Module 9. Integrating with DBT workflows
Embed compoundable patterns directly into your DBT project structure.
12 chapters in this module
- Macro packaging
- Source freshness tests
- Assertion rule reuse
- Exposure tagging
- Lineage tracking
- Documentation automation
- Project-level defaults
- Environment parity
- CI/CD integration
- Model health scoring
- Test coverage targets
- Deployment gate logic
Module 10. Stakeholder alignment on reusable specs
Get buy-in for standards that speed up delivery and reduce revisions.
12 chapters in this module
- Business owner onboarding
- Definition of ready
- Feedback timing
- Scope boundary agreement
- Change control process
- UAT sign-off
- SLA documentation
- Exception tracking
- Priority triage
- Escalation path
- Revision cycle reduction
- Expectation alignment
Module 11. Maintaining velocity with quality
Balance the need for speed with the need for trust in reusable components.
12 chapters in this module
- Automated regression
- Model health dashboard
- Drift detection alerts
- Version compatibility
- Backfill cost awareness
- Performance baseline
- Schema change impact
- Downstream alerting
- Ownership clarity
- Hotfix process
- Review frequency
- Decommission process
Module 12. Growing influence through compoundable work
Position yourself as the go-to builder of reliable, reusable data assets.
12 chapters in this module
- Showcasing reuse impact
- Internal case studies
- Presentation format
- Leadership messaging
- Peer mentoring
- Onboarding enablement
- Pattern review board
- Recognition pathways
- Promotion case building
- Thought leadership
- Community of practice
- External sharing criteria
How this maps to your situation
- When starting a new DBT project
- After delivering a complex pipeline
- Before a cross-team handoff
- During quarterly model review
Before vs. after
Before
Each new pipeline starts from scratch, with inconsistent patterns and repeated stakeholder alignment.
After
Every delivery strengthens a growing library of trusted specs, cutting scoping time and increasing trust.
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 90 minutes per module, self-paced over 6-8 weeks.
If nothing changes
Continuing to build one-off models means missed opportunities to reduce rework, increase velocity, and position yourself as a builder of systems, not just deliverables.
How this compares to the alternatives
Unlike generic data modelling courses, this program focuses on creating compoundable assets, not just correctness. Competitor courses teach best practices; this one teaches how to build a growing, personal IP library that makes future work faster and more influential.
Frequently asked
Who is this course for?
Data engineers and analysts who work in DBT and Snowflake and want to turn their work into reusable, trusted assets that accelerate future projects.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Do I need prior experience with IP libraries?
No, the course starts with how to identify your first reusable patterns from existing work.
$199 one-time. Approximately 90 minutes per module, self-paced over 6-8 weeks..
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