{"id":23317926,"url":"https://github.com/dakshsammi/arkaid","last_synced_at":"2026-04-09T01:31:04.117Z","repository":{"id":267507595,"uuid":"901467546","full_name":"DakshSammi/Arkaid","owner":"DakshSammi","description":"Arkaid is a game performance analytics platform developed for the Information Integration Architecture Course - CSE656 (IIIT Delhi). 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It employs a data warehouse approach to analyze and integrate gaming data from multiple sources, providing insights through an AI-powered interface.\n\n## Project Overview\n\nArkaid combines data from multiple gaming platforms and sources, utilizing ETL processes and materialized views to create a unified analytical platform. The project features natural language query capabilities powered by TogetherAI, enabling users to easily access and analyze gaming performance data.\n\n## Key Features\n\n- **Multi-Source Data Integration**: Combines data from Steam and Epic Games platforms\n- **Advanced Analytics**: Game performance metrics, player behavior analysis, and content creator insights\n- **Natural Language Queries**: AI-powered conversion of natural language to SQL queries\n- **Real-time Data Processing**: ETL pipelines for continuous data updates\n- **Interactive Interface**: Web-based interface for data exploration and analysis\n\n## Architecture\n\nThe project is organized into three main modules:\n\n### 1. Data Generation\nLocated in `/Data_Generation`\n- Generates and manages gaming-related datasets\n- Creates realistic test data for development and testing\n- Handles data for games, players, developers, publishers, and content creators\n- [More details](Data_Generation/README.md)\n\n### 2. ETL (Extract, Transform, Load)\nLocated in `/ETL`\n- Manages data flow between different databases\n- Creates and maintains materialized views\n- Handles schema matching and data transformation\n- Ensures data consistency and integrity\n- [More details](ETL/README.md)\n\n### 3. Interface\nLocated in `/Interface`\n- Provides web-based user interface\n- Integrates TogetherAI for natural language processing\n- Executes and visualizes query results\n- Manages database connections and query optimization\n- [More details](Interface/README.md)\n\n## Database Structure\n\nThe project utilizes three PostgreSQL databases:\n1. **DB1**: Epic Games data source\n2. **DB2**: Steam data source\n3. **DB3**: Centralized warehouse with materialized views\n\n## Technologies Used\n\n- **Backend**: Python, PostgreSQL\n- **ETL**: Custom Python ETL framework\n- **Frontend**: Flask, HTML/CSS\n- **AI Integration**: TogetherAI API\n- **Data Processing**: pandas, numpy\n- **Database**: psycopg2, SQLAlchemy\n\n## Setup\n\n1. Clone the repository:\n```bash\ngit clone https://github.com/lakshaybhushan/Arkaid-IIA.git\ncd Arkaid-IIA\n```\n\n2. Set up each module:\n```bash\n# Set up Data Generation\ncd Data_Generation\npip install -r requirements.txt\n\n# Set up ETL\ncd ../ETL\ncp .env.example .env\n# Edit .env with your database credentials\n\n# Set up Interface\ncd ../Interface\ncp .env.example .env\n# Edit .env with your database and TogetherAI API credentials\n```\n\n3. Configure databases:\n```bash\ncd Interface\npython db_config_generator.py\npython connection_tester.py\n```\n\n4. Start the application:\n```bash\n# In the Interface directory\npython app.py\n```\n\n## Usage\n\n1. **Data Generation**:\n   - Generate test data using the scripts in the Data_Generation module\n   - Update and maintain data sources as needed\n\n2. **ETL Processes**:\n   - Run ETL scripts to process and transform data\n   - Manage materialized views for optimized queries\n\n3. **Interface**:\n   - Access the web interface at `http://localhost:4321`\n   - Use natural language to query the database\n   - Explore predefined queries and visualizations\n\n\n## Contributors\n- [Lakshay Bhushan](https://github.com/lakshaybhushan)\n- [Daksh Sammi](https://github.com/dakshsammi)\n- [Sameer Budhiraja](https://github.com/Sameer-Budhiraja)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdakshsammi%2Farkaid","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdakshsammi%2Farkaid","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdakshsammi%2Farkaid/lists"}