E-commerce_Sales_Dashboard

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E-commerce_Sales_Dashboard

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# E-Commerce Store Analysis

## Description

This repository contains a Power Bi dashboard of an E-commerce store to answer questions about the data. The insights of the dashboard can be found in the results.txt file.  This repository can be used as a starting point for anyone who wants to learn how to use Power Bi to analyze data.

## Screenshot

![dashboard preview](https://github.com/avishek09/E-Commerce-Store-Analysis-/assets/75924699/5151c585-882b-4db4-b324-a8cc63256fb4)

## Installation

To run this project on your machine you need to install <a href="https://powerbi.microsoft.com/en-us/downloads/">Microsoft Power Bi</a>.

<!-- ## Usage

Provide instructions and examples for use. Include screenshots as needed.

To add a screenshot, create an `assets/images` folder in your repository and upload your screenshot to it. Then, using the relative filepath, add it to your README using the following syntax:

```md
    ![schema](https://raw.githubusercontent.com/yashoda-krishna/E-commerce_Sales_Dashboard/main/MusicDatabaseSchema.png)
    ``` -->

## Tools

* Microsoft Power BI

## Credits

Throughout the development of this project, I have sought inspiration from a pivotal video source: https://youtu.be/6cV3OwFrOkk

## Badges

![Power Bi](https://img.shields.io/badge/power_bi-F2C811?style=for-the-badge&logo=powerbi&logoColor=black)
![YouTube](https://img.shields.io/badge/YouTube-%23FF0000.svg?style=for-the-badge&logo=YouTube&logoColor=white)

## Project Learnings

* Created an interactive dashboard to track and analyze online sales data.
* Used complex parameters to drill down in worksheet and customization using filters and slicers.
* Created connections, joined new tables, did calculations to manipulate data, and enabled user-driven parameters for visualization.
* Used different types of customized visualization (bar chart, pie chart, donut chart, clustered bar chart, scatter chart, line chart, area chart, map, slicers, etc)

## Conclusion

The project was successful in answering the set of questions about an E-commerce Store's performance. The results of the project can be found in result.txt file.

<!--## How to Contribute

If you created an application or package and would like other developers to contribute it, you can include guidelines for how to do so. The [Contributor Covenant](https://www.contributor-covenant.org/) is an industry standard, but you can always write your own if you'd prefer.-->

<!-- ## Questions Answered

The following questions are answered by the project:

* What are the most popular genres of music?
* What are the most popular artists?
* What are the most popular songs?
* What are the average prices of different types of music?
* What are the most popular countries for music purchases?

## Data Set

The data set used for this project is available on GitHub. The data set contains information about the store's customers, music, and sales.

## Results

The results of the project are as follows:

* The most popular genre of music is pop.
* The most popular artist is Taylor Swift.
* The most popular song is "Despacito" by Luis Fonsi and Daddy Yankee.
* The average price of an album is $10.
* The most popular country for music purchases is the United States.

## Conclusion

The project was successful in answering the set of questions about the store's business performance. The results of the project can be used by the store to make decisions about its marketing and product offerings.

I hope this is helpful! -->
"# Product_Sales_Analysis"

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