ECE graduate transitioning into Data Analytics, with hands-on BFSI (housing finance) domain experience from an apprenticeship at LIC Housing Finance Ltd. Currently completing a structured DA training program (Spreadsheets → SQL → Power BI → Business Analytics → Python).
Each project below is deliberately rebuilt across multiple tools using the same dataset and business questions, to demonstrate range rather than one-off exercises. Every case study ends in a concrete number or recommendation, not just a chart.
| # | Project | Business Question | Tools Used | Status |
|---|---|---|---|---|
| 1 | Cash Flow Intelligence Dashboard | Where is money leaking across accounts, and what's the underlying financial health score? | Spreadsheets → SQL → Power BI → Python | In Progress |
| 2 | Retail / E-commerce Sales Analysis | Which products/regions/segments actually drive revenue, and where's the untapped opportunity? | Spreadsheets → SQL → Power BI → Python | Planned |
| 3 | HR Attrition Analysis | Which departments/roles have the highest attrition, and what's driving it? | Spreadsheets → SQL → Power BI → Python | Planned |
| 4 | Marketing Campaign Performance Analysis | Which channels/campaigns deliver real ROI vs. which are losing money? | Spreadsheets → SQL → Power BI → Python | Planned |
| 5 | Loan Default / Credit Risk Analysis | Which borrower segments carry the highest default risk? (BFSI differentiator project) | Spreadsheets → SQL → Power BI → Python | Planned |
Each project folder follows the same structure, so a reviewer can navigate any of them the same way:
XX-project-name/
├── README.md <- Problem statement, approach, findings, recommendation
├── data/
│ ├── raw/ <- Source data, left intentionally unclean (source of truth)
│ └── cleaned/ <- Cleaned/transformed data
├── spreadsheets/ <- Excel/Sheets workbooks
├── sql/ <- Queries, schema, SQL-based analysis
├── powerbi/ <- .pbix files, dashboard screenshots
├── python/ <- Notebooks/scripts for deeper analysis
└── assets/ <- Charts, dashboard images used in the README
Data cleaning · Spreadsheet modeling · SQL · Power BI · Python (pandas) · Business/financial analysis · BFSI domain context
- B.Tech Electronics & Communication Engineering, M.S. Ramaiah University of Applied Sciences (2024)
- Apprentice, Sanction Department — LIC Housing Finance Ltd
- Data Analytics training — Sharpener Tech
- LinkedIn: www.linkedin.com/in/tejashwini-s-24488b41a
- Email: aryantejashwini@gmail.com