Defines and manages calculated dimensions and virtual columns in Honeydew semantic models using SQL and YAML.
The attribute-creation skill provides a structured workflow for data engineers and analysts to define, update, and manage calculated attributes within Honeydew entities. It guides Claude through building precise SQL expressions for major data warehouses like Snowflake, Databricks, and BigQuery, ensuring that business logic is defined once and governed centrally. By enforcing best practices such as fully qualified column names, explicit data typing, and mandatory validation, this skill helps maintain a clean, reusable semantic layer that translates complex raw data into business-friendly dimensions for BI tools.
주요 기능
010 GitHub stars
02Direct integration with MCP tools for model discovery and object management
03Mandatory validation workflow to test attribute logic and data accuracy
04Multi-dialect SQL expression building for Snowflake, Databricks, and BigQuery
05Automated YAML schema generation for Honeydew entity updates
06Step-by-step creation of calculated dimensions and virtual row-level columns
사용 사례
01Creating reusable business logic like net price or customer tiers across a semantic model
02Implementing row-level calculations such as date truncations, window functions, and string formatting
03Normalizing raw or encoded data into business-friendly labels for BI consumption
