🎯 Aspiring Business and Data Analyst skilled in Python, SQL, Power BI, and Excel 📍 India • 📫 LinkedIn |
- Languages & Tools: Python, SQL, Power BI, Excel, Git, MySQL
- Libraries & Packages: Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn
- Concepts: Data Cleaning, EDA, Data Visualization, Machine Learning, Dashboarding
- Other: DAX, Star Schema Modeling, Row-Level Security, GitHub Collaboration
Power BI · Pandas · Data Visualization · Business Intelligence
- Cleaned and preprocessed ATM transaction dataset using Pandas
- Built an interactive Power BI dashboard with dynamic filters, slicers, and visual storytelling
- Analyzed ATM performance: revenue, gross profit, uptime, and transaction trends
- Generated actionable insights for cost optimization, cash planning, and operational efficiency
- Focused on state-wise analysis, highlighting top-performing and underperforming regions
Power BI · SQL · Python · DAX · Business Intelligence
- Cleaned and modeled Superstore data for sales analysis using Pandas and Power Query
- Built Power BI dashboard with DAX measures, custom visuals, and row-level security
- Extracted business insights with SQL: top customers, regional performance, profit trends
- Collaborated with Avishek Das for dashboard design and storytelling
Web Scraping · SQL · EDA · Pandas · BeautifulSoup
- Scraped book data (title, price, rating, availability) using BeautifulSoup
- Stored cleaned data in CSV and queried with MySQL for insights
- Performed EDA with Pandas, Seaborn to visualize pricing and rating trends
Python · Scikit-learn · Power BI · Pandas · Team Project
- Built a customer churn prediction pipeline with 87% accuracy using Logistic Regression
- Cleaned and transformed data with Pandas & NumPy
- Designed Power BI dashboards with KPIs, filters, and RLS
- Collaborated in a 3-member team managing Power BI and GitHub
Python · Pandas · Seaborn · EDA · Visualization
- Analyzed 1M+ NFT transactions to uncover pricing patterns and seasonal trends
- Cleaned data using Pandas and visualized insights with line charts, box plots, and heatmaps
- Highlighted top-performing collections, expensive assets, and market behavior
Python · Web Scraping · SQL · Data Visualization
- Scraped quotes, authors, and tags from multiple pages using BeautifulSoup
- Structured data into MySQL and ran SQL queries for insights (e.g., top authors, most used tags)
- Visualized quote lengths, common words, and tag distributions using Seaborn & Matplotlib
“Learning never exhausts the mind. Keep building, keep analyzing.”