🎯 Aspiring Data Analyst with hands-on experience in Python, SQL, and Power BI.
I enjoy working with data to uncover insights, understand business performance, and support data-driven decision-making.
- Data Cleaning & Exploratory Data Analysis (EDA)
- SQL Queries (Joins, Aggregations, Subqueries)
- Dashboarding & Visualization (Power BI, Excel)
- Business Insights & KPI Analysis
- SSMS and MySQL
- MS Excel
📦 Advanced E-Commerce Analytics
Built an end-to-end data analytics pipeline using Python, SQL, and Power BI on 1000+ records. Performed customer segmentation using RFM analysis and K-Means clustering. Developed a forecasting model (ARIMA) to predict revenue trends. Implemented product recommendation system using Apriori algorithm. Derived insights to improve customer retention and revenue optimization.
📊 E-Commerce Sales Performance Analysis
Analyzed 1200+ transaction records generating ₹41M+ revenue to evaluate business performance. Performed data cleaning in Python and SQL-based analysis for product, region, and customer insights. Built an interactive Power BI dashboard tracking KPIs like revenue, profit, and AOV. Identified top-performing products, regional trends, and underperforming categories.
🏦 Banking Transactions & Customer Analysis
Analyzed ₹12M+ transaction data to understand customer behavior and financial patterns. Used Python for data preprocessing and SQL for structured analysis. Built dashboard to track transaction trends, loan approvals, and branch performance. Identified high-value customers and key revenue-driving segments.
👩💼 Employee Attrition Analysis
Analyzed 400+ employee records to identify key factors driving attrition. Performed feature engineering (salary groups, experience groups) and SQL-based analysis. Built Power BI dashboard to visualize attrition trends across departments and job satisfaction. Identified major drivers such as low salary, poor work-life balance, and low job satisfaction.
🏥 Healthcare Data Analysis
Analyzed 500+ hospital records to understand patient trends, disease patterns, and department performance. Performed data cleaning and feature engineering (length of stay, age groups) using Python. Used SQL to analyze patient distribution, treatment costs, and department-wise performance. Built Power BI dashboard to visualize patient trends, doctor workload, and disease distribution. Provided insights for improving hospital resource allocation and operational efficiency.
📊 Financial & Business KPI Dashboard
Developed interactive dashboard using Excel and Power BI to track revenue, profit, and margins. Performed data cleaning, transformation, and feature engineering using Excel functions. Visualized region-wise and product-wise performance trends. Provided insights for improving profitability and optimizing business strategy.
💼 HR Operations & Payroll Analytics Dashboard
Analyzed 150,000+ workforce, payroll, expense claim, and travel records using Python and Power BI. Performed data cleaning, feature engineering, and dataset integration to evaluate payroll expenditure, workforce distribution, reimbursement patterns, and travel spending trends. Built interactive dashboards with DAX measures to monitor payroll costs, claim approval rates, employee distribution, and operational expenses. Identified key cost drivers and generated insights to support HR and financial decision-making.
- Preparing for Data Analyst roles
- Strengthening SQL and problem-solving skills
- Practicing real-world business case questions