Etl

A comprehensive reference guide for dbt (data build tool) analytics engineering. It covers model organization using the medallion architecture (staging, intermediate, marts layers), testing strategies, documentation practices, incremental model patterns, and common dbt commands. Ideal for data engineers building transformation pipelines.

A comprehensive data engineering skill that teaches production-ready Apache Airflow DAG patterns including TaskFlow API, dynamic DAG generation, sensors, branching logic, and error handling. Also covers dbt transformation patterns, Spark optimization techniques, and data quality frameworks with Great Expectations.

This skill provides AI assistants with deep knowledge about the Addax open-source ETL tool. It covers the project's architecture, plugin system for 20+ data sources (MySQL, PostgreSQL, MongoDB, Kafka, HDFS, etc.), job configuration format, data transformation capabilities, and development guidelines for building custom reader/writer plugins.