Skip to content

This project 🍕 explores the Pizza Runner business using SQL Server. It involves data cleaning, analysis of pizza metrics, customer experience, and pricing optimization, aiming to improve business efficiency and decision-making.

Notifications You must be signed in to change notification settings

ElaWajdzik/SQL_Challenge_Case_Study_2---Pizza-Runner

Repository files navigation

I practice my SQL skills with the #8WeekSQLChallenge prepared by Danny Ma. Thank you Danny for the excellent case study. If you are also looking for materials to improve your SQL skills you can find it here and try it yourself.

Case Study #2: 🍕 Pizza Runner

Image Danny's Diner - the taste of success

Table of Contents

Business Case

Did you know that over 115 million kilograms of pizza is consumed daily worldwide??? (Well according to Wikipedia anyway…)

Danny was scrolling through his Instagram feed when something really caught his eye - “80s Retro Styling and Pizza Is The Future!”

Danny was sold on the idea, but he knew that pizza alone was not going to help him get seed funding to expand his new Pizza Empire - so he had one more genius idea to combine with it - he was going to Uberize it - and so Pizza Runner was launched!

Danny started by recruiting “runners” to deliver fresh pizza from Pizza Runner Headquarters (otherwise known as Danny’s house) and also maxed out his credit card to pay freelance developers to build a mobile app to accept orders from customers.

Relationship Diagram

graf2

Available Data

All datasets exist in database schema.

Table 1: runners

runner_id registration_date
1 2021-01-01
2 2021-01-03
3 2021-01-08
4 2021-01-15

Table 2: customer_orders

order_id customer_id pizza_id exclusions extras order_time
1 101 1 2021-01-01 18:05:02
2 101 1 2021-01-01 19:00:52
3 102 1 2021-01-02 23:51:23
3 102 2 NaN 2021-01-02 23:51:23
4 103 1 4 2021-01-04 13:23:46
4 103 1 4 2021-01-04 13:23:46
4 103 2 4 2021-01-04 13:23:46
5 104 1 null 1 2021-01-08 21:00:29
6 101 2 null null 2021-01-08 21:03:13
7 105 2 null 1 2021-01-08 21:20:29
8 102 1 null null 2021-01-09 23:54:33
9 103 1 4 1, 5 2021-01-10 11:22:59
10 104 1 null null 2021-01-11 18:34:49
10 104 1 2, 6 1, 4 2021-01-11 18:34:49

Table 3: runner_orders

order_id runner_id pickup_time distance duration cancellation
1 1 2021-01-01 18:15:34 20km 32 minutes
2 1 2021-01-01 19:10:54 20km 27 minutes
3 1 2021-01-03 00:12:37 13.4km 20 mins NaN
4 2 2021-01-04 13:53:03 23.4 40 NaN
5 3 2021-01-08 21:10:57 10 15 NaN
6 3 null null null Restaurant Cancellation
7 2 2020-01-08 21:30:45 25km 25mins null
8 2 2020-01-10 00:15:02 23.4 km 15 minute null
9 2 null null null Customer Cancellation
10 1 2020-01-11 18:50:20 10km 10minutes null

Table 4: pizza_names

pizza_id pizza_name
1 Meat Lovers
2 Vegetarian

Table 5: pizza_recipes

pizza_id toppings
1 1, 2, 3, 4, 5, 6, 8, 10
2 4, 6, 7, 9, 11, 12

Table 6: pizza_toppings

topping_id topping_name
1 Bacon
2 BBQ Sauce
3 Beef
4 Cheese
5 Chicken
6 Mushrooms
7 Onions
8 Pepperoni
9 Peppers
10 Salami
11 Tomatoes
12 Tomato Sauce

Case Study Questions

This case study includes questions about:



Thank you for your attention! 🫶️

Thank you in advance for reading. If you have any comments on my work, please let me know. My email address is ela.wajdzik@gmail.com.

About

This project 🍕 explores the Pizza Runner business using SQL Server. It involves data cleaning, analysis of pizza metrics, customer experience, and pricing optimization, aiming to improve business efficiency and decision-making.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages