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https://github.com/agungbudiwirawan/e-commerce_analysis_using_sql

The objective of this project is to provide an analysis of Olist Store (Brazilian E-commerce) sales.
https://github.com/agungbudiwirawan/e-commerce_analysis_using_sql

data-analysis data-science e-commerce e-commerce-project microsoft-sql-server sql sql-server

Last synced: 25 days ago
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The objective of this project is to provide an analysis of Olist Store (Brazilian E-commerce) sales.

Host: GitHub
URL: https://github.com/agungbudiwirawan/e-commerce_analysis_using_sql
Owner: agungbudiwirawan
Created: 2023-01-09T03:04:07.000Z (almost 2 years ago)
Default Branch: main
Last Pushed: 2023-01-09T06:43:12.000Z (almost 2 years ago)
Last Synced: 2024-11-27T13:26:19.553Z (about 1 month ago)
Topics: data-analysis, data-science, e-commerce, e-commerce-project, microsoft-sql-server, sql, sql-server
Homepage:
Size: 309 KB
Stars: 3
Watchers: 1
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: README.md

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README

# e-commerce_analysis_using_sql
## Overview
The objective of this project is to provide an analysis of [Olist Store](https://olist.com/pt-br/) (Brazilian E-commerce) sales.
## Dataset
The dataset can be downloaded at [Brazilian E-Commerce Public Dataset by Olist](https://www.kaggle.com/datasets/olistbr/brazilian-ecommerce?select=olist_geolocation_dataset.csv) from [kaggle.com](https://www.kaggle.com/). The dataset has information of 100k orders from 2016 to 2018 made at multiple marketplaces in Brazil.
## Tool
- Microsoft SQL Server
## Problem
1. Top 10 best selling products
2. Top 10 best-selling product categories
3. Top 10 products by profit
4. Top 10 product categories by profit
5. Total profit per year
6. Total profit per month
7. Top 10 customers by order quantity
8. Top 10 sellers by order quantity
9. Top 10 cities by profit
10. Most commonly used payment types
11. The product categoriy that has a review score of less than 3
12. Sellers who have a review score less than 3 and total reviews greater than 10
## Algorithm
1. Create database and use database
2. Import dataset to SQL Server
3. Analyze using [sql query](https://github.com/agungbudiwirawan/e-commerce_analysis_using_sql/blob/main/e-commerce_analysis_using_sql.sql)
- Problem 1: Top 10 best selling products

![alt text](https://github.com/agungbudiwirawan/e-commerce_analysis_using_sql/blob/main/Output/1st%20query%20output.JPG)
- Problem 2: Top 10 best-selling product categories

![alt text](https://github.com/agungbudiwirawan/e-commerce_analysis_using_sql/blob/main/Output/2nd%20query%20output.JPG)
- Problem 3: Top 10 products by profit

![alt text](https://github.com/agungbudiwirawan/e-commerce_analysis_using_sql/blob/main/Output/3rd%20query%20output.JPG)
- Problem 4: Top 10 product categories by profit

![alt text](https://github.com/agungbudiwirawan/e-commerce_analysis_using_sql/blob/main/Output/4th%20query%20output.JPG)
- Problem 5: Total profit per year

![alt text](https://github.com/agungbudiwirawan/e-commerce_analysis_using_sql/blob/main/Output/5th%20query%20output.JPG)
- Problem 6: Total profit per month

![alt text](https://github.com/agungbudiwirawan/e-commerce_analysis_using_sql/blob/main/Output/6th%20query%20output.JPG)
- Problem 7: Top 10 customers by order quantity

![alt text](https://github.com/agungbudiwirawan/e-commerce_analysis_using_sql/blob/main/Output/7th%20query%20output.JPG)
- Problem 8: Top 10 sellers by order quantity

![alt text](https://github.com/agungbudiwirawan/e-commerce_analysis_using_sql/blob/main/Output/8th%20query%20output.JPG)
- Problem 9: Top 10 cities by profit

![alt text](https://github.com/agungbudiwirawan/e-commerce_analysis_using_sql/blob/main/Output/9th%20query%20output.JPG)
- Problem 10: Most commonly used payment types

![alt text](https://github.com/agungbudiwirawan/e-commerce_analysis_using_sql/blob/main/Output/10th%20query%20output.JPG)
- Problem 11: The product categoriy that has a review score of less than 3

![alt text](https://github.com/agungbudiwirawan/e-commerce_analysis_using_sql/blob/main/Output/11th%20query%20output.JPG)
- Problem 12: Sellers who have a review score less than 3 and total reviews greater than 10

![alt text](https://github.com/agungbudiwirawan/e-commerce_analysis_using_sql/blob/main/Output/12th%20query%20output.JPG)

## Thank you!