{"repo":"mattiasthalen/adventure-works","free":true,"listed":false,"github":"https://github.com/mattiasthalen/adventure-works","clone":"git clone https://github.com/mattiasthalen/adventure-works.git","description":"Modern serverless lakehouse implementing HOOK methodology, Unified Star Schema (USS), and Analytical Data Storage System (ADSS) principles on Adventure Works. Features programmatic model generation, event-enhanced Puppini bridges, and temporal resolution across DAS/DAB/DAR layers.","language":"Python","stars":126,"topics":["data-architecture","data-engineering","data-modeling","data-warehouse","dimensional-modeling","duckdb","iceberg","lakehouse","serverless","sqlmesh"],"license":"GPL-3.0","category":"data-pipelines","readme_excerpt":"Serverless Lakehouse Overview This project demonstrates a modern, serverless approach to data warehousing that combines the simplicity of local file storage with the power of cloud-native architectures. It implements a three-layer data architecture using innovative modeling techniques that prioritize business alignment and analytical flexibility. The solution: 1. Extracts data from source systems via dlt 2. Loads raw data to Iceberg tables (DAS layer) 3. Transforms data into a business-aligned model using HOOK methodology (DAB layer) 4. Creates a unified analytical structure using Puppini Bridges (DAR layer) 5. Provides visualization through Streamlit dashboards All data is stored locally in ./lakehouse (which could be replaced by a cloud storage bucket in production). Streamlit Dashboard Architecture Principles This lakehouse follows the \"Analytical Data Storage System\" design pattern by Patrik Lager, consisting of three distinct layers: 1. DAS - Data According To System : Raw, unaltered data ingested from source systems with minimal transformation. This layer preserves the original data structure and serves as a foundation for auditing and lineage. 2. DAB - Data According To Business : Data transformed and aligned with business concepts using the HOOK methodology. This layer bridges technical implementation with business understanding. 3. DAR - Data According To Requirements : Data structured to support specific analytical needs using the Unified Star Schema pattern. This l","default_branch":null,"files":null,"tree":[],"storefront":"/r/mattiasthalen","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/mattiasthalen/adventure-works/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}