Analytics Engineering (dbt & Data Warehousing) Roadmap — Step-by-step…
Modeling business logic in the warehouse using dbt: dimensional modeling, testing, documentation and the semantic layer
The Analytics Engineering (dbt & Data Warehousing) roadmap
- Analytics Engineering Fundamentals — beginner
- Cloud Data Warehouse Fundamentals — beginner
- Cloud Data Warehouse Fundamentals — beginner
- Columnar Storage and Query Performance — beginner
- Comparing Snowflake, BigQuery and Redshift — beginner
- Warehouse Compute and Scaling Models — beginner
- Connecting Tools to a Warehouse — beginner
- dbt Fundamentals — beginner
- dbt Project Structure — beginner
- Models, Sources and Refs — beginner
- Materializations Explained — beginner
- The dbt Compile and Run Cycle — beginner
- dbt Cloud vs dbt Core — beginner
- SQL for Analytics Engineering — beginner
- SQL Patterns for Analytics Engineering — beginner
- Writing Readable, Maintainable SQL — beginner
- Common Table Expressions and Modularity — beginner
- Window Functions for Analytics — beginner
- Performance-Aware SQL Writing — beginner
- Building dbt Models — beginner
- Building Your First dbt Models — beginner
- Staging, Intermediate and Mart Layers — beginner
- Naming Conventions for dbt Projects — beginner
- Sources and Freshness Checks — beginner
- Seeds and Reference Data — beginner
- Structuring a Large dbt Project — beginner
- Dimensional Modeling — beginner
- Dimensional Modeling Fundamentals — beginner
- Star Schema vs Snowflake Schema — beginner
- Slowly Changing Dimensions — beginner
- Fact Table Grain and Design — beginner
- Modeling One Big Table (OBT) vs Star Schema — beginner
- Incremental Models in dbt — beginner
- Incremental Models in dbt — beginner
- Choosing an Incremental Strategy — beginner
- Handling Late-Arriving Data in Incremental Models — beginner
- Full Refresh vs Incremental Runs — beginner
- Debugging Incremental Model Issues — beginner
- Macros and Jinja Templating — beginner
- Jinja Templating in dbt — beginner
- Writing Reusable Macros — beginner
- Control Flow in dbt (if/for statements) — beginner
- Packages and dbt Hub — beginner
- When Macros Add Complexity Instead of Value — beginner
- Testing and Data Quality in dbt — beginner
- dbt Testing Fundamentals — beginner
- Writing Custom Data Tests — beginner
- Singular vs Generic Tests — beginner
- Testing Strategy for Large Projects — beginner
- Data Quality Frameworks Beyond dbt (Great Expectations, Soda) — beginner
- Building a Testing Culture Around a dbt Project — beginner
- Documentation and Lineage — beginner
- Documenting dbt Models — beginner
- Generating and Hosting dbt Docs — beginner
- Data Lineage in dbt — beginner
- Column-Level Lineage — beginner
- Keeping Documentation Current — beginner
- The Semantic Layer and Metrics — beginner
- What a Semantic Layer Solves — beginner
- dbt Semantic Layer and MetricFlow — beginner
- Metric Definitions and Governance — beginner
- Connecting BI Tools to a Semantic Layer — beginner
- Avoiding Metric Drift Across Tools — beginner
- Orchestrating dbt in Production — beginner
- Running dbt in Production — beginner
- Orchestrating dbt with Airflow or Dagster — beginner
- dbt Cloud Scheduling — beginner
- Handling dbt Run Failures — beginner
- Environment Management (Dev, Staging, Prod) — beginner
- Warehouse Performance and Cost Optimization — beginner
- Warehouse Query Performance Fundamentals — beginner
- Clustering and Partitioning in the Warehouse — beginner
- Materialization Strategy for Performance — beginner
- Warehouse Cost Optimization — beginner
- Query Result Caching — beginner
- Monitoring Warehouse Spend and Usage — beginner
- CI/CD for Analytics Engineering — beginner
- CI/CD Fundamentals for Analytics Engineering — beginner
- Running dbt Tests in CI — beginner
- Slim CI and Deferral — beginner
- Code Review Practices for dbt Projects — beginner
- Version Control Workflows for Analytics Engineering — beginner
- Collaborating with Analysts and Stakeholders — beginner
- Working with Data Analysts — beginner
- Gathering Requirements for New Models — beginner
- Communicating Data Model Changes — beginner
- Office Hours and Self-Service Analytics — beginner
- Building Trust in Data Through Consistent Modeling — beginner
- Advanced dbt Patterns — beginner
- Multi-Project dbt Setups (Mesh) — beginner
- Exposures and Downstream Dependencies — beginner
- Custom Materializations — beginner
- Python Models in dbt — beginner
- dbt Performance at Very Large Scale — beginner
- Career and Capstone — advanced