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chocolatesalesanalysis's Introduction

ChocolateSalesAnalysis

SQL + PowerBI - Sales Analysis & Visualisation Project

Awesome Chocolates Sales Report

Awesome Chocolate Co. uses data-driven insights for growth. This project aims to analyze sales data to answer key queries and return actionable trends and patterns.

Data
Link To Database In Github

Tables:
geo: Geographical data.
people: Salespeople information.
products: Product details and pricing.
sales: Sales transactions.

Tools
MySQL for data management and querying.
PowerBI for data visualization.

Methodology

  • Formulate specific analytical questions.
  • Execute SQL queries for data extraction.
  • Visualise data in PowerBI.

SQL Queries
Top Selling Products: Based on quantity.

SELECT Product, SUM(Boxes) as Total_Boxes_Sold 
FROM products 
JOIN sales ON products.PID = sales.PID
GROUP BY Product
ORDER BY Total_Boxes_Sold DESC;

Top Selling Products: Based on revenue.

SELECT Product, SUM(Amount) AS Total_Sales
FROM products 
JOIN sales ON products.PID = sales.PID
GROUP BY Product
ORDER BY Total_Sales DESC;

Sales by Region: Highlighting top-performing regions.

SELECT Region, SUM(Amount) as Total_Sales 
FROM geo 
JOIN sales ON geo.GeoID = sales.GeoID
GROUP BY Region
ORDER BY Total_Sales DESC;

More Questions To Answer
Top-performing Salespersons: Based on revenue generated.
Sales Trends: Monthly and daily patterns over time.
Customer Management: Number of unique customers per salesperson.
Profit Margins: Products delivering the best profitability.
Seasonal Patterns: Monthly fluctuations in sales.

For all the business questions and their corresponding queries, see the chocolates_queries.sql file

Dashboard Awesome Chocolates Sales Report

For visualised, interactable insights, view the dashboard here.

Recommendations
Market Expansion: Capitalize on the success in Canada and New Zealand by further penetrating these markets with tailored marketing strategies and product offerings.
USA Sales Strategy: Investigate why USA sales are not proportional to its population and adapt accordingly.
Product Focus: Build on the success of 'After Nines' with new variations.
Individual Recognition: Reward top salespersons like Andria Kimpton for continued motivation.

Acknowledgements
Link to dataset: https://chandoo.org/wp/learn-sql-for-data-analysis/

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