E-Commerce’s Sales Data Analysis

Project Overview

This project involved the analysis of sales data in the e-commerce industry using tools such as Tableau, R Studio, and Excel. The primary focus was on performing exploratory data analysis (EDA) and regression techniques using the R programming language. Through EDA, the data was thoroughly examined to uncover patterns, relationships, and insights. Regression techniques were then applied to analyze and interpret the data, enabling the extraction of meaningful information. Generalized linear methods were utilized to efficiently interpret the data and address strategic and operational questions. Correlation analysis and logistic regression methods were employed to improve predictive outcomes and understand factors impacting sales in the e-commerce industry. Overall, the project aimed to leverage data analysis techniques to gain insights into e-commerce sales data and enhance predictive capabilities.

I showcase my expertise in data analysis and visualization, with a focus on the e-commerce industry. I have utilized tools such as Tableau, R Studio, and Excel to analyze sales data, perform exploratory data analysis, and apply regression techniques. Through projects, I have identified least selling products, analyzed region profitability by category, examined category distribution by sales, explored profit and loss by state, and evaluated shipping time for improved supply chain management. My portfolio demonstrates my ability to derive meaningful insights and make data-driven decisions to drive business growth and customer satisfaction.