dbt Model Builder

About

Streamlines the creation of robust dbt models by automating the development of staging layers, fact tables, dimension tables, and analytical marts. It enforces strict data engineering best practices, including per-model YAML documentation, External Parquet partitioning for large datasets, and the latest dbt 1.10+ test syntax. By guiding users through complex workflows like Slowly Changing Dimensions (SCD Type 2) and the 2×2 stat model quadrant, it ensures that analytics repositories remain modular, highly performant, and consistently documented.

Key Features

• External Parquet table optimization with custom partitioning logic
• SCD Type 2 pattern support for historical data tracking
• Advanced testing configurations using dbt 1.10+ data_tests syntax
• Standardized templates for staging, facts, dimensions, and analytical marts
• 0 GitHub stars
• Implementation of Kimball dimensional modeling and 2x2 stat architectures

Use Cases

• Designing a new analytics-ready data layer from raw source data
• Updating existing dbt projects to comply with modern testing and documentation standards
• Converting complex statistical event logs into structured fact and dimension tables