dbt Analytics Engineering Certification

Module 1: Introduction to Analytics Engineering

• Analytics engineering fundamentals
• Analytics engineering lifecycle
• Data engineering vs analytics engineering
• Modern data stack
• Transformation workflows
• Analytics engineering responsibilities

Module 2: Introduction to dbt

• dbt fundamentals
• Core capabilities
• dbt workflow
• SQL-based transformations
• Project concepts
• Common use cases

Module 3: Setting Up a dbt Project

• Project initialization
• Project structure
• Configuration files
• Profiles
• Warehouse connections
• Development environment

Module 4: Building dbt Models

• SQL models
• SELECT statements
• Model files
• Model execution
• Model dependencies
• Transformation logic

Module 5: Sources & Source Data

• Source definitions
• Source configuration
• Source references
• Source freshness
• Raw data management
• Source documentation

Module 6: Model References & Dependencies

• ref() function
• Dependency management
• Directed acyclic graphs
• Model relationships
• Lineage
• Dependency visualization

Module 7: Data Modelling with dbt

• Staging models
• Intermediate models
• Mart models
• Fact tables
• Dimension tables
• Layered architecture

Module 8: Materializations

• Views
• Tables
• Incremental models
• Ephemeral models
• Materialization selection
• Performance considerations

Module 9: Testing in dbt

• Data tests
• Unique tests
• Not-null tests
• Relationship tests
• Accepted values
• Custom tests

Module 10: Data Quality Management

• Data validation
• Quality rules
• Data consistency
• Quality monitoring
• Test failures
• Issue resolution

Module 11: Documentation

• Model documentation
• Column descriptions
• Source documentation
• Documentation generation
• Data discovery
• Documentation maintenance

Module 12: Jinja Fundamentals

• Jinja syntax
• Variables
• Expressions
• Control structures
• Dynamic SQL
• Reusable logic

Module 13: Macros

• Macro fundamentals
• Creating macros
• Macro parameters
• Reusable SQL
• Utility functions
• Macro organization

Module 14: Seeds & Static Data

• Seed files
• CSV datasets
• Loading seeds
• Reference datasets
• Configuration
• Seed management

Module 15: Snapshots

• Snapshot concepts
• Historical tracking
• Slowly changing dimensions
• Change detection
• Snapshot configuration
• Historical analysis

Module 16: Incremental Models

• Incremental processing
• Incremental strategies
• Filtering new records
• Unique keys
• Model updates
• Performance optimization

Module 17: dbt Packages

• Package management
• Reusable packages
• Package dependencies
• Utility packages
• Package configuration
• Dependency management

Module 18: Advanced dbt Development

• Model contracts
• Reusable patterns
• Environment variables
• Hooks
• Advanced configuration
• Project organization

Module 19: CI/CD for dbt

• Version control
• Git workflows
• Development branches
• Automated testing
• Continuous integration
• Deployment workflows

Module 20: Orchestration & Production Workflows

• Job scheduling
• Workflow orchestration
• Dependency execution
• Production runs
• Failure handling
• Monitoring

Module 21: dbt Performance & Best Practices

• Efficient SQL
• Model optimization
• Warehouse performance
• Project conventions
• Maintainability
• Scalability

Module 22: Practical Analytics Engineering Project

• Source configuration
• Staging models
• Transformation layers
• Data tests
• Documentation
• Analytics mart development