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The client approached us with the goal of developing an advanced web application designed to streamline and enhance metadata management for large-scale data systems. Their primary objectives included automating metadata processing, improving data visibility through lineage extraction, and integrating AI-driven assistance to boost productivity for data and development teams. The platform needed to support various complex functions such as metadata scaling, column lineage visualization, AI-assisted code generation, and an intelligent chatbot for handling data-related queries. In addition, the client required seamless API integrations and a scalable infrastructure to ensure high performance and reliability across all modules.
Solution
We built a powerful and scalable web application that delivers a comprehensive suite of metadata and AI-driven automation tools. The solution enables users to upload files, connect databases, and generate detailed metadata descriptions through both crowdsourcing and GenAI integration. For lineage visualization, we implemented ER diagram generation to clearly map data flow and dependencies. The Code Concierge feature assists developers with AI-powered code generation, comparison, and merging, while the Data Concierge chatbot handles data-related inquiries and automates routine tasks. All major operations are supported by robust REST APIs, ensuring smooth and efficient data processing. Built using Angular, Laravel, MySQL, and Python, and hosted on IBM Cloud, the application provides both scalability and performance. The result is an intelligent, high-performing platform that improves efficiency, accuracy, and user engagement while significantly reducing manual effort for data teams.
Tech Stack
- Angular
- GitHub
- IBM Cloud
- Jenkins
- Laravel
- MySQL
- Python
- Watsonx AI
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