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https://github.com/mayankyadav23/amazon-sales-data-analysis


https://github.com/mayankyadav23/amazon-sales-data-analysis

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# Amazon Sales Data Analysis 📊✨

[![GitHub](https://img.shields.io/badge/GitHub-black?style=for-the-badge&logo=github)](https://github.com/mayankyadav23) 

![Power BI](https://img.shields.io/badge/Power%20BI-F2C94C?style=for-the-badge&logo=powerbi)

![iNeuron.AI](https://img.shields.io/badge/iNeuron-blue?style=for-the-badge&logo=ineuron)

![Feature Engineering](https://img.shields.io/badge/Feature%20Engineering-4B9CD3?style=for-the-badge&logo=data-science)

![Data Analysis](https://img.shields.io/badge/Data%20Analysis-FF5733?style=for-the-badge&logo=chart-line)

![Data Modeling](https://img.shields.io/badge/Data%20Modeling-FFC300?style=for-the-badge&logo=data-driven)



## About 📝

This project aims to explore the Amazon Sales data to understand top-performing branches and products, sales trends of different products, and customer behavior. The goal is to analyze how sales strategies can be improved and optimized. The dataset was provided by iNeuron to complete the project and extract various insights. A Power BI Dashboard has been developed to present insights into Amazon sales trends, highlighting region-specific and item-specific analyses across different years, quarters, months, and days. This comprehensive dashboard offers detailed insights into various sales trends.



## Purposes of the Project 🎯

The major aim of this project is to gain insight into the sales data of Amazon to understand the different factors that affect sales across various branches.



## Problem Statement 📈

Sales management has gained importance to meet increasing competition and the need for improved distribution methods to reduce costs and increase profits. Sales management is crucial in a commercial and business enterprise. This project includes performing ETL (Extract-Transform-Load) on the Amazon dataset to analyze sales trends—monthly, yearly, and more. It identifies key metrics and factors, revealing meaningful relationships between attributes.



## Tools Used 🛠️

- **Power BI**: For creating interactive dashboards and visualizations.

- **Microsoft Excel**: For data manipulation and analysis.

- **MySQL**: For database management and querying.



## Analysis List 🔍

### Sales Analysis

This analysis addresses the sales trends of products. The results will help measure the effectiveness of each sales strategy applied by the business and identify necessary modifications to enhance sales.



### Product Analysis

Conduct analysis on the data to understand the different product lines, identifying which lines perform best and which need improvement.



### Customer Analysis

This analysis aims to uncover various customer segments, purchase trends, and the profitability of each segment.



## Approach Used 🚀

### Data Wrangling

This initial step involves inspecting the data to ensure NULL values and missing values are detected. Data replacement methods are applied to replace these values.



### Build a Database

1. Create tables and insert data.

2. Select columns with NULL values; ensure that there are no NULL values in our database, as the tables were created with NOT NULL constraints for each field.



### Feature Engineering

Generate new columns from existing ones, including:

- **Year**: Extracted year from transaction dates (2012, 2013, 2014, 2015) to determine the year with the most sales and profit.

- **Month Name**: Extracted month names from transaction dates (Jan, Feb, Mar...) to identify the month with the highest sales and profit.

- **Day Name**: Extracted day names from transaction dates (Mon, Tue, Wed...) to analyze which day of the week each branch is busiest.



### Exploratory Data Analysis (EDA)

Perform exploratory data analysis to answer the listed questions and aims of this project.



## Dashboard 🎥

- **Watch the complete Dashboard video**: [Video Link](https://example.com/video) 

- **Check out the dashboard**: [Dashboard](https://example.com/dashboard) 



## Documentation 📚

- **High Level Document**: [Download Here](https://example.com/high-level-doc) 

- **Low Level Document**: [Download Here](https://example.com/low-level-doc) 

- **Architecture Diagram**: ![Architecture](https://example.com/architecture-diagram.png) 

- **Wireframe**: ![Wireframe](https://example.com/wireframe.png) 

- **Report**: [Download Report](https://example.com/report) 



## Conclusion 🎉

This project provides valuable insights into Amazon's sales data, aiding in the optimization of sales strategies and enhancing decision-making processes. By understanding sales trends and customer behavior, businesses can better allocate resources and improve profitability.



## 📧 Contact Information

You can reach me via email:  

[![Email](https://img.shields.io/badge/[email protected]?style=for-the-badge&logo=gmail)](mailto:[email protected])



Feel free to connect with me on [LinkedIn](https://www.linkedin.com/in/mayankyadv) for more insights and updates! 🌐