Checking the performance of campaigns on different marketing channels

Decathlon Sales Analysis in R

This contains some of the data analysis projects I have worked on in excel.

A comprehensive Python project for sales data analysis, including data preprocessing, customer segmentation, cohort analysis, and market study. Visualize trends by day, month, and region to uncover actionable business insights and improve decision-making. Suitable for retail businesses looking to optimize performance.

This project aims to predict (and prevent) customer churn in the telecom industry with our advanced analytics and machine Learning.

(2012-13) Java based sales management tool that enables you to identify weak areas in sales process.

Analyze monthly sales of an e-commerce.

Predictive Analytics for Sales

The Global Superstore Sales Analysis repository showcases a comprehensive Power BI dashboard that provides valuable insights into sales performance. This project is designed to present key information and trends to stakeholders, enabling informed decision-making.

Provides a systematic approach for forecasting sales data based on historical quarterly sales figures.

Exploratory analysis of Diwali sales data

The "Harnessing SQL for Sales Insights and Improvement" project involved comprehensive analysis of sales data extracted from SQL Server, imported into MySQL for data preparation, cleaning, normalization, and in-depth analysis using various SQL commands and functions.

SQL project focused on analyzing retail sales data, querying databases to uncover trends, performance metrics, and actionable insights.

Developed a Power BI Sales Performance and Customer Insights Dashboard to visualize key sales metrics, analyze customer behavior, and identify growth opportunities. The dashboard provided insights into sales trends, product performance, customer retention, and geographic distribution.

superstore Sales Analysis and Dashboard Using Power BI

Black Thursday is a system that's able to load, parse, search, and execute business intelligence queries against the data from a typical e-commerce business. Built in Ruby

Automated Dashboards, fetching the data via SQL queries and user-interface being MS Excel.