📍 Gujarat, India | 📊 Data Analyst | 🤖 AI-Augmented Analyst
PostgreSQL CTEs Window Functions pgAdmin 4
End-to-end SQL business analysis on a 14-table relational database.
- 8 business-case queries covering sales performance, customer retention, employee KPIs & inventory
- Identified a VIP customer with 31 orders over 570 days — ordering at 3.4x the dataset average
- Employee performance ranking using
RANK(),CTEs,LAG()for QoQ revenue,SUM() OVER()for running totals - Product restock alert system using
CASE WHENurgency labels to flag supply gaps proactively
Python Pandas Matplotlib Seaborn Jupyter Notebook
Full exploratory data analysis pipeline on a real Indian e-commerce dataset.
- Complete cleaning pipeline: null handling, dtype fixing, deduplication, integrity validation
- Category-level revenue breakdown + price vs. rating correlation across product segments
- Applied Min-Max Scaling and Z-Score Standardization following a strict load → validate → clean → normalize workflow
- Visual summaries built for non-technical stakeholders
SQL Problem Solving Query Optimization
Completed all 50 SQL problems on LeetCode's curated SQL Study Plan.
- Covered JOINs, aggregations, subqueries, window functions, CTEs, and string manipulation
- Solved problems spanning easy to hard difficulty — consistently focusing on clean, readable query logic
- Documented solutions and learnings as LinkedIn posts to reinforce concepts through teaching
| Category | Tools |
|---|---|
| Data & Querying | SQL (PostgreSQL · MySQL · MS SQL Server), Excel |
| Programming | Python, Pandas, NumPy, Matplotlib, Seaborn |
| BI & Visualization | Power BI, Jupyter Notebook, |
| Data Modeling | Relational schema design, ER diagrams, normalization |
| Dev Tools | Git, GitHub, VS Code, pycharm, Notion |
| Gen AI & Productivity | Claude AI, Claude Code, Prompt Engineering, AI Workflow Automation |
| Concepts | EDA, Data Cleaning, Window Functions, Data Validation, Business Reporting |
- 🏆 SQL (Advanced) — HackerRank
2026 - 🏆 Data Analysis with Python — IBM · Coursera
2026 - 🏆 Data Modeling — Pragmatic works
2026 - 🔜 Microsoft Power BI (PL-300) — Exam scheduled (in progress)
- SQL first — I validate data structure before writing a single line of analysis
- Clean before you trust — every dataset goes through null checks, dtype fixes, and deduplication before EDA
- Multi-dialect SQL — comfortable switching between PostgreSQL, MySQL, and MS SQL Server depending on the stack
- AI-augmented, not AI-dependent — I use Claude and Claude Code to work faster, but I write and understand every line myself
- Document as I go — Notion for project tracking, GitHub for version control, READMEs a recruiter can actually read
Data Analyst roles at analytics-first companies where I can work on real business problems, build clean pipelines, and grow fast.
Currently: Completed Bachelors (2026) · Preparing for PL-300
"Data is only as good as the questions you ask it."