Rimi Singha

📊 Meesho Sales Analysis – 2025  This project focuses on analyzing Meesho’s 2025 sales data to identify sales trends, top-performing categories, and revenue contribution across different segments. I cleaned and processed raw sales data, handled missing values, and performed exploratory data analysis to understand customer purchasing behavior.

📊 Mall Sales & Profit Dashboard | Data Analytics | Excel This project analyzes City Centre Mall’s performance using multi-year sales, revenue, and customer data. Dashboards highlight revenue trends, category performance, regional sales, inventory patterns, and customer ratings. Insights show strong growth from 2021–2024, with technology leading sales, supporting data-driven decisions and future retail growth.

Developed a SQL-based Ola Cab Analysis project to manage and analyze ride booking data for business insights. Designed relational database structures and wrote advanced SQL queries using joins, aggregations, and subqueries to evaluate ride performance, revenue trends, and customer behavior. The project improves data accuracy, supports operational monitoring, and enables data-driven decision-making to enhance service efficiency and overall business performance.

Developed a SQL-based Retail Sales Analysis system to extract, transform, and analyze transactional data for business insights. Designed relational tables, applied joins, aggregations, and subqueries to evaluate sales performance, customer behavior, and product trends. Created optimized queries to support reporting and decision-making. The project improves data accuracy, enables performance monitoring, and provides actionable insights to enhance revenue growth and operational efficiency.

Developed an interactive Power BI dashboard for Via Cab to analyze revenue, trip performance, and driver efficiency. Integrated multiple datasets using a star schema to enable KPI monitoring, cancellation analysis, and demand insights. The solution supports data-driven decision-making, operational optimization, and revenue enhancement through clear, scalable business intelligence reporting.

Designed and developed an interactive Power BI dashboard to analyze diabetes patient data and identify critical health risk indicators. Applied data cleaning, transformation, and star schema modeling to ensure efficient analysis. Created DAX measures and KPI visualizations to monitor BMI, glucose, and blood pressure trends. The dashboard delivers actionable insights, supports early risk identification, and enables data-driven decision-making to enhance preventive healthcare planning and improve overall patient management.