TCS-2021/Data-Mining-Project
Apr 2025 – Apr 2025
1 Month active
Languages Used
Python
Technical Skills
Algorithm IntegrationData AnalysisData MiningPythonStreamlitSystem Path Configuration
Nitish Krishna
PROFILE
Nitish Krishna
During April 2025, 21pt40@psgtech.ac.in developed the foundational analytics dashboard for the TCS-2021/Data-Mining-Project, focusing on a scalable, multi-module architecture. They implemented a modular Streamlit-based UI with a wide layout, navigation sidebar, and system path configuration to streamline future analytics module integration. Their work included resolving merge conflicts and preparing the frontend for SPADE algorithm integration, enabling seamless frontend-backend communication for prescriptive analytics. Using Python, Streamlit, and data mining techniques, they established a robust project structure that reduces onboarding time for new modules and supports consistent development practices, demonstrating depth in both architectural planning and technical implementation.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
2
Lines of code
352
Activity Months1
Your Network
25 people
Work History
April 2025
2 Commits • 2 Features
Apr 1, 2025April 2025: Delivered foundational analytics platform groundwork for the Data-Mining-Project, establishing a scalable, multi-module analytics dashboard and enabling future prescriptive analytics via SPADE integration. Key outcomes include a new Analytics Dashboard Skeleton with a modular project structure and Streamlit-based UI, navigation, styling, and robust module import path configuration to support easy module addition. Resolved merge conflicts and completed SPADE integration groundwork in Prescriptive Analysis 1 frontend to pave the way for backend access to SPADE functionality. These efforts reduce time-to-market for new analytics modules, improve consistency across modules, and set up for future performance and prescriptive analytics capabilities. Technologies demonstrated include Python, Streamlit, Git merge conflict resolution, and frontend-backend integration planning.
2 Commits • 2 Features
Apr 1, 2025April 2025: Delivered foundational analytics platform groundwork for the Data-Mining-Project, establishing a scalable, multi-module analytics dashboard and enabling future prescriptive analytics via SPADE integration. Key outcomes include a new Analytics Dashboard Skeleton with a modular project structure and Streamlit-based UI, navigation, styling, and robust module import path configuration to support easy module addition. Resolved merge conflicts and completed SPADE integration groundwork in Prescriptive Analysis 1 frontend to pave the way for backend access to SPADE functionality. These efforts reduce time-to-market for new analytics modules, improve consistency across modules, and set up for future performance and prescriptive analytics capabilities. Technologies demonstrated include Python, Streamlit, Git merge conflict resolution, and frontend-backend integration planning.
April 2025
Activity
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Quality Metrics
Correctness75.0%
Maintainability70.0%
Architecture75.0%
Performance50.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Algorithm IntegrationData AnalysisData MiningPythonStreamlitSystem Path Configuration
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