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
Developed the foundational analytics platform for the TCS-2021/Data-Mining-Project, establishing a scalable, multi-module dashboard using Python and Streamlit. The work focused on creating a modular project structure with a wide layout, navigation sidebar, and system path configuration to streamline the addition of future analytics modules. Integrated SPADE algorithm groundwork into the Prescriptive Analysis 1 frontend, enabling frontend-backend connectivity for prescriptive analytics. Addressed merge conflicts and ensured consistent module import paths, supporting maintainability and extensibility. This approach reduced time-to-market for new features and set up a robust framework for future data analysis and algorithm integration within the repository.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
2
Lines of code
352
Activity Months1
Your Network
26 peopleSame Organization
@psgtech.ac.in6
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
Repositories Contributed To
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