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https://github.com/edjoukou/pizza-sales-report

A data analysis project using SQL with MySQL database
https://github.com/edjoukou/pizza-sales-report

analysis data mysql powerbi visualization

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A data analysis project using SQL with MySQL database

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README 

        
# Pizza-Sales-Report



pizza



## Project Overview

This data analysis project focuses on evaluating a Pizza Hut's sales performance throughout 2015. By examining different aspects of the sales data, the goal is to uncover trends, offer data-driven recommendations, and gain a more comprehensive understanding of the shop's overall performance.



## Data source

The dataset utilized for this project was collected on September, 2024, and sourced from the kaggle website. It is available for download via the following web link: pizza sales



The dataset is organized into four tables: **order_details**, **orders**, **pizzas**, **pizza_types**. A detailed data description of each variables of these two tables is available at the same web link



## Tools

- MySQL Workbench 8.0 to create an instance of MySQL an connect it to python

- Jupyter notebook IDE for data analysis

- Power BI for data visualization



## Data cleaning and preparation

In the initial phase, the following tasks were performed:

1. data loading and inspections

2. Handling data types



## Exploratory Data Analysis

Here are the business questions investigated as part of the 



1. What is the total number of orders placed?

2. What are the total sales revenue generated?

3. How do the total number of orders change over time?

4. What is the average value of each order?

5. Which pizza type is the top-selling item?

6. How are sales distributed across different pizza categories?

7. How do order volumes vary by day of the week?

8. What is the distribution of orders by hour of the day?



## Data Analysis

it has been performed on jupyter notebook, please check uploaded the pizzahut file uploaded



## Results/ Findings

1. The total sales revenue for 2015 amounted to 817,860 USD.  

2. The Thai Chicken Pizza was the shop's best-selling item, generating 43,434 USD in sales.  

3. The Classic Pizza category was the most popular, bringing in 220,053 USD in revenue.  

4. The first day of each month was identified as the peak day for orders.  

5. The busiest hours were found to be between 11:00 AM and 12:00 PM, and from 5:00 PM to 6:00 PM.  



pizza44



## Recommendations

Based on the analysis, we recommend the following actions:

Based on the sales performance data, here are a few recommendations to enhance business growth:



- Focus on Top-Selling Items: Since the Thai Chicken Pizza is the best-seller, consider offering promotions, combo deals, or highlighting it in marketing campaigns to further boost its sales.



- Expand the Classic Pizza Category: Given its popularity and high revenue, explore adding new varieties to the Classic Pizza menu, or offer limited-time flavors to attract more customers.



- Leverage Peak Sales Days: Since the first day of the month is the busiest for orders, consider launching special discounts or loyalty rewards to capitalize on this trend and incentivize repeat purchases.



- Optimize Staffing During Peak Hours: With peak times between 11 AM–12 PM and 5 PM–6 PM, ensure enough staff is available to handle the rush efficiently and maintain customer satisfaction.



- Target Marketing During Peak Hours: Implement time-specific promotions or special offers during the busiest hours to further increase sales and encourage customers to visit during those times.