{"repo":"MultiTonic/thinking-dataset","free":true,"listed":false,"github":"https://github.com/MultiTonic/thinking-dataset","clone":"git clone https://github.com/MultiTonic/thinking-dataset.git","description":"Creating a Thinking Dataset: Leveraging Real-World Data for Strategic Business Insights and STaR Case Study Generation.","language":"Python","stars":11,"topics":["database-operations","ai","business-analytics","business-intelligence","compliance","dataset-generation","datasets","governance","government","synthetic-dataset-generation"],"license":"MIT","category":"databases-storage","readme_excerpt":"Thinking Dataset: Leveraging Real-World Data for Strategic Business Insights Table of Contents - Overview - Features - Installation - Usage - Quick Start - Project Structure - Contributing - Resources - License - Citations - Acknowledgements - Contact Overview Thinking Dataset leverages real-world data and efficient pipelines for business insights. We integrate robust data workflows (PDF to SQL ingestion), tactical TDD (details), and a streamlined SQLite design (details). Multi-stage AI generates STaR case studies for actionable strategies. Features - 🔄 End-to-End Pipeline : Download, process, transform, and store large datasets. - 💾 SQLite Backend : Lightweight, fast, and easy to manage, with optional Parquet. - ✅ Comprehensive Testing : Thorough TDD coverage and validation checks. - 🖥️ Flexible CLI : Modular Click commands for quick execution of tasks. - 🔀 Data Transformation : Granular pipes for cleaning, merging, and deriving data. - 📚 STaR Case Studies : Generate synthetic scenarios alongside real data for deeper insights. - ⚡ Parallel Execution : Efficiently process big data with optional concurrency. - 🔒 Secure Config : Manage environment variables discretely with .env files. Quick Start Prerequisites - Python 3.12 or later - Git - A cloud-based account (e.g., Huggingface ) or a GPU ( RTX 3090 or greater) for processing, or both Setup 1. Clone the repository: 2. Install uv package manager: First add the package into the global environment: Then add uv tools direc","default_branch":null,"files":null,"tree":[],"storefront":"/r/MultiTonic","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/MultiTonic/thinking-dataset/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."}