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Saintpius/Exploratory-Data-Analysis-of-International-Breweries-brands

Domain:

socioeconomic

Record type:

dataset
Creator:
Sai
Host:
This analysis explained the detailed transactions per countries for the International_Breweries in 2 Anglophone and 3 Francophone Africa countries between the period of 3 years (2017-2019) using sql # Exploratory Data Analysis of International Breweries brands Exploratory Data Analysis of the International Breweries brands across 2 Anglophone and 3 Francophone Africa countries between the period of 3 years (2017-2019) using SQL. ## OVERVIEW OF THE PROJECT The International Breweries dataset is a collection of data regarding various brewery products in various Africa countries, namely: Nigeria, Ghana, Senegal, Benin and Togo respectively. The dataset is stored in a CSV file and contains information such as sales reps for each country with their sales ID and email, brands, plant cost, unit price, quantity, cost, profit, countries, region, years and months covered by the report. The goal of this project is to use SQL to analyze and extract insights from the International Breweries dataset. This may an in-depth price, profit and countries analysis to help us understand the acceptability of each of the product, profit margin, and lots more across the regions of the various countries involved within the period of 3 years (2017, 2018, 2019. The project will require a basic understanding of SQL and the final deliverable for the project will be a report summarizing the key findings and insights from the data analysis. Overall, the International Breweries dataset provides a great opportunity to practice SQL skills and gain insight into the world of brewing. ## About the dataset This dataset (International_Breweries.csv) contains the data about the different products of the international breweries namely Trophy, Budweiser, Castle lite, Eagle lager, Hero, Beta malt and Grand malt which are available Nigeria, Ghana, Togo, Benin and Senegal between the period of 2017 and 2019. ### The columns contained in the dataset are : 1. Sales ID 2. Sales rep 3. Emails 5. Brands 6. Plant cost 7. Unit price 8. Quantity 9. Cost 10. Profit 11. Countries 12. Region 13. Months 14. Years ## BREAKDOWN OF THE SQL ANALYSIS Database named "Brewery" was created, inside which I creat …

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