Subhankar Das
Subhankar Das Aspiring Data Analyst · Kolkata, IN
Open to Data Analyst roles
📍 Kolkata, India · IST

Subhankar Das

Aspiring Data Analyst focused on SQL & data visualization.

Passionate data analyst from Kolkata, India, currently mastering SQL, data visualization, and analytics fundamentals. Building a strong foundation in PostgreSQL, Excel, and Power BI through hands-on projects and continuous learning. Ready to contribute analytical insights to innovative teams.

SQL · PostgreSQL · Window functions Excel · Pivot tables · Power BI dashboards

Featured Projects

End-to-end analytics work from real business-style datasets.

Independent projects
📚 Bookstore Dashboard
E‑Commerce Profitability Analysis
SQL · Power BI · Excel · Mar 2024

Consolidated online retail data from multiple product, category, and regional tables using SQL joins and transformations, replicating enterprise data warehouse workflows. Analyzed 10,000+ transactions to find revenue and profit margin patterns and identified a 15% margin improvement opportunity, then built a Power BI dashboard with KPI cards, drill‑down slicers, and cohort views for stakeholders.

🛒 Sales Performance
SaaS Revenue & Churn Analysis
SQL · Power BI · Excel · Jan 2024

Integrated subscription billing and usage data to calculate MRR, ARR, and churn metrics using SQL transformations. Performed cohort-based retention analysis on 5,000+ subscribers, uncovering 23% revenue leakage in at‑risk segments. Built a Power BI report highlighting churn drivers and growth opportunities, with recommendations projected to reduce churn by 18% and increase ARR by 12%.

💻 SQL Portfolio
Loan Default Risk Analysis
SQL · Power BI · Excel · Nov 2023

Analyzed 8,000+ loan applications across income, credit‑to‑income ratio, employment history, and age using SQL and Excel. Developed a risk‑scoring methodology based on historical default rates and created a Power BI risk assessment dashboard to visualize applicant risk distribution. Optimized SQL transformations to automate credit‑scoring steps, reducing processing time by 35%.