Turning 180,000-row spreadsheets
into decisions leadership acts on.
I build the SQL, Python and Power BI pipelines that find the money hiding in messy transactional data — then present it as a business case, not just a chart.
Finance-trained, dashboard-obsessed.
I'm a data analyst who came to analytics through finance — an MBA in Finance that taught me to ask "so what does this mean for the business" before I ask "what chart should I use."
That combination is why my projects don't stop at a dashboard: on a 184K-row retail dataset, I didn't just visualize discounts, returns and stockouts — I quantified ₹3.94M in recoverable leakage and turned it into a stakeholder-ready business case.
On the technical side, I work across SQL Server, Python, Power BI, Tableau and increasingly Microsoft Fabric — Lakehouse, Data Warehouse, DirectLake and Semantic Models — a cloud-analytics skill set that's uncommon this early in a career.
Tools I query, model and ship with.
Languages & Querying
Databases
Visualization & BI
Cloud & Tools
Projects that found real money.
Each one starts with messy source data and ends with a decision someone could act on.
Retail Chain Profit Leakage & Demand Optimization
Engineered an end-to-end analytics pipeline on a 184K-row, 7-sheet retail dataset — a relational SQL schema across 6 tables, CTE and window-function queries, and a 5-page Power BI dashboard with DAX-driven RFM segments. Applied K-Means clustering in Python to split customers into Champion, Loyal, At-Risk and One-Time Buyer cohorts.
Swiggy Food Delivery Analytics
Architected a complete Microsoft Fabric pipeline — Lakehouse → Data Warehouse → Semantic Model → DirectLake Power BI report — a cloud-native build that's rare at fresher level. Used real-time DirectLake refresh to surface top-performing food categories and city-level demand patterns.
Retail Performance & Customer Analytics (RetailNova)
Ran a full Python EDA pipeline — outlier detection, type correction, feature engineering — then wrote 20+ SQL queries covering cohort retention, revenue trends and product profitability. Delivered a 5-page interactive Power BI report with RFM segmentation and store-level KPIs.
A few more repos worth a look.
stock-market-analysis
Automated stock analysis system for NSE-listed stocks with technical indicators, built in Python.
github.com ↗sales-analytics-powerbi
Interactive Power BI dashboard analyzing ₹19.8M in sales across regions, products and customers, with DAX measures and data quality checks.
github.com ↗customer-behaviour-analysis
Jupyter Notebook project digging into customer behaviour patterns to inform retention and targeting decisions.
github.com ↗Where the work happened.
Data Analyst Intern
Built SQL queries and Power BI visualizations for an end-to-end Retail Performance and Behavioral Analytics project, converting customer and sales data into actionable business insights.
Data Analyst Intern
Delivered the Retail Chain Profit Leakage & Demand Optimization project end-to-end using Python, SQL and Power BI, producing analysis used for business decision support.
Assistant Supervisor
Coordinated cross-functional teams on daily operational workflows, resolved process bottlenecks and reported operational KPIs to management.
Digital Marketing Intern
Increased website traffic by 30% and social media engagement by 20% through data-driven SEO, content strategy and user-behaviour analysis.
Agricultural Research Intern
Organized 100+ farmer training workshops on sustainable agricultural practices and modern techniques.
Credentials behind the dashboards.
MBA — Finance
B.Com — Computer Applications
Let's turn your data into a decision.
Open to Data Analyst roles and freelance dashboard work.