
Worked on the TCS-2021/Data-Mining-Project, focusing on backend and frontend improvements to enhance performance and maintainability. Introduced caching for data cube generation using Python and Streamlit, which reduced recomputation time and improved dashboard responsiveness. Refactored the application to establish a clear separation between frontend and backend components, with the backend dedicated to data processing and cube generation while the frontend managed the user interface. Emphasized scalable development by stabilizing and restructuring the codebase, leveraging skills in data modeling, data warehousing, and caching. No major bugs were addressed during this period, with efforts concentrated on feature delivery and architectural refinement.
April 2025 monthly summary for TCS-2021/Data-Mining-Project: Delivered caching and architectural improvements that enhance performance and maintainability. Focused on business value by reducing recomputation time for data cubes and enabling clearer frontend-backend separation. No major bugs fixed; stabilization and refactoring round out feature delivery to support faster dashboards and scalable development.
April 2025 monthly summary for TCS-2021/Data-Mining-Project: Delivered caching and architectural improvements that enhance performance and maintainability. Focused on business value by reducing recomputation time for data cubes and enabling clearer frontend-backend separation. No major bugs fixed; stabilization and refactoring round out feature delivery to support faster dashboards and scalable development.

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