Business Problem:

The business problem asks four key questions:

1. How many customers do we have each day? Are there any peak hours?

2. How many pizzas are typically in an order? Do we have any bestsellers?

3. How much money did we make this year? Can we identify any seasonality in the sales?

4. Are there any pizzas we should take off the menu, or any promotions we could leverage.

What Was Done:

With the aid of a robust multi-table pizza sales dataset sourced from Maven Playground, comprising approximately 50,000 records, I successfully crafted an intuitive and comprehensive dashboard using Power BI.

The initial step involved thorough data cleaning using Power Query, streamlining the dataset for optimal analysis. Subsequently, I delved into data modeling and employed DAX functions to define key measures, enabling profound insights into the data.

I incorporated supplementary columns and an indispensable "Date" table to facilitate an in-depth examination of seasonal trends and patterns in the pizza sales data.

Key Insights:

In analyzing the pizza sales data, several key insights emerge.

On average, the company receives 60 orders per day, with peak hours observed between 12 pm and 9 pm. The months of July and August see the highest sales, aligning with the peak days of Thursday, Friday, and Saturday. Most orders consist of an average of 2 pizzas.

Among the pizzas offered, the best-sellers include barbeque chicken pizza, California chicken pizza, classic deluxe pizza, spicy Italian pizza, and Thai chicken pizza. Conversely, the least popular pizzas are spinach pesto pizza, mediterranean pizza, spinach supreme pizza, green garden pizza, and brie carre pizza.

In total, the sales revenue amounts to an impressive $817,860.