SQL 

Scenario: I was given the statistics of a pizza parlor and was asked to find some defining information regarding their sales and procedure using SQL (Bigquery) . I was given pizza_id, order_id, pizza_name_id, quantity, order date, order_time, unit_price, total_price, pizza_size, pizza_category, pizza_ingredients, and pizza_name. I started with removing the order_id, pizza_id, and pizza_name_id to remove any identifying information gathered from the customer for their privacy and normalizing / cleaning the data. I started looking at what day had the most orders placed consistently, what types of pizzas were the highest selling, and what ingredients were most widely seen in the ingredients list of those pizzas.

Questions asked:

1. What is the most profitable product the pizza parlor sells?

2. What is the most common day of delivery?

3. What is the most popular ingredient used in pizzas?

Questions answered:

1. The most profitable pizza and most sold is the classic category which includes any pizza with red sauce and classic toppings  

• Of this category large pizzas were most sold and the most profitable

2. The most common delivery day is Friday, and the least ordered day is Sunday

   • I believe this is due to convenience and get togethers happening during the weekend, and not wanting to over buy for the proceeding week

3. The most used ingredient within the pizza parlor is garlic which must be included in everything, and the least used ingredient is thyme

Recommendations :

1. Market to large classic pizza orders since they are already the most sought after to make the ordering scenario more simple, and include a slight increase in pizzas not in that category

2. Market a savings deal on Sundays or the middle of the week incentivising convenience for a busy week and that pizza is not solely for get togethers

3. Garlic is a very consumed product in this business model, and may be able to find a better supplier for both quality and price. May look into a wholesale method to store garlic at today’s price for use in the future 

License information: here