https://github.com/nafisalawalidris/international-breweries

This GitHub readme provides an overview of data analysis using SQL on the International Breweries dataset, including dataset description, analysis questions, example SQL queries, and key insights derived from the analysis.
https://github.com/nafisalawalidris/international-breweries

data-analysis insights international-breweries-dataset queries sql

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This GitHub readme provides an overview of data analysis using SQL on the International Breweries dataset, including dataset description, analysis questions, example SQL queries, and key insights derived from the analysis.

• Host: GitHub
• URL: https://github.com/nafisalawalidris/international-breweries
• Owner: nafisalawalidris
• Created: 2023-06-17T22:26:35.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2023-06-17T22:32:59.000Z (over 1 year ago)
• Last Synced: 2024-11-22T21:16:37.329Z (2 months ago)
• Topics: data-analysis, insights, international-breweries-dataset, queries, sql
• Homepage:
• Size: 109 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        


  
Data Analysis using SQL - International Breweries Dataset

  

  
This repository contains SQL queries and analysis performed on the International Breweries dataset. The dataset consists of information related to sales, brands, regions and sales representatives.

  

  
Dataset Description

  

  
The International Breweries dataset includes the following columns:

  

  


    
SALES_REP: The name of the sales representative

    
BRANDS: The brand of the product

    
QUANTITY: The quantity of products sold

    
COSTS: The cost of the products

    
REGION: The region where the sales occurred

    
YEAR: The year of the sales

  

  

  
Analysis Questions

  

  


    
What are the total sales made by each sales representative?

    
Which brand had the highest sales in each year?

    
Which region recorded the highest quantity of goods in each quarter?

    
What is the average cost of products sold in each year?

  

  

  
SQL Queries

  

  
Here are some example SQL queries used for data analysis:

  

  

    

SELECT SALES_REP, SUM(QUANTITY) AS TOTAL_SALES

FROM breweries

GROUP BY SALES_REP;


SELECT YEAR, BRANDS, MAX(QUANTITY) AS HIGHEST_SALES

FROM breweries

GROUP BY YEAR;

SELECT YEAR, QUARTER, REGION, MAX(QUANTITY) AS HIGHEST_QUANTITY

FROM breweries

GROUP BY YEAR, QUARTER;

SELECT YEAR, AVG(COSTS) AS AVERAGE_COST

FROM breweries

GROUP BY YEAR;

    

  

  

  
Conclusion

  

  
Through SQL analysis on the International Breweries dataset, we can gain insights into sales performance, popular brands, regional trends, and cost analysis. These insights can help inform decision-making and drive business growth.