Pizza House Sales Analysis --SQL Project

mayanksri461994 548 views 20 slides Aug 12, 2024
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About This Presentation

To analyze pizza sales data to provide actionable insights on sales performance, customer preferences, and revenue generation.


Slide Content

SQL Project
A Project on Pizza House Sales Analysis
https://www.linkedin.com/in/mayank-srivastava-6a8421105/

PROJECT SUMMARY
OBJECTIVE
To analyze pizza sales data to:

provide actionable insights on sales
performance,

customer preferences, and

revenue generation.
01
FEATURES OF THE TOPIC

Sub Query

Group By

Cumulative sum, Rank

Visualizations
02
ABOUT THE DATASET

Analyzing sales records from a pizza
restaurant, spanning one year.

Dataset has 48,620 sales
transactions to analyze.
02
TOOLS USED

MySQLfor data querying and
manipulation

Python(Pandas, Matplotlib,
Seaborn)
04

Connecting to
pizza_houseDatabase

DATA SCHEMA

Retrieve the total number of orders
placed.

Calculate the total revenue generated
from pizza sales.

Identify the highest-priced pizza.

Identify the most common pizza size
ordered.

List the top 5 most ordered pizza types
along with their quantities.

Join the necessary tables to find the total
quantity of each pizza category ordered.

Determine the distribution of orders by
hour of the day.

Join relevant tables to find the category-
wise distribution of pizzas.

Group the orders by date and calculate the
average number of pizzas ordered per day.

Determine the top 3 most ordered pizza
types based on revenue.

Calculate the percentage contribution of
each pizza type to total revenue.

Analyze the cumulative revenue
generated over time.

Determine the top 3 most ordered pizza types
based on revenue for each pizza category.

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Do you have any questions?

[email protected]

https://www.linkedin.com/in/mayank-srivastava-6a84211054

https://www.hackerrank.com/profile/mayanksri461994

https://github.com/Mayank4694

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