Tools used in this project
Plato Pizza

Power BI

About this project

The Project is to craft data stories by analyzing data and addressing important questions, such as the busiest days and times, the amount of pizzas made during peak periods, best-selling and worst-selling pizzas, average order value, and how well the seating capacity is being utilized. Join me in transforming data into actionable insights and assisting Plato's Pizza in its success!

Assumptions were used in the analysis:

Pizza Serving

  1. Size: Small: 1 Person
  2. Medium: 2 People
  3. 3 people in a large
  4. 1 hour is the average dining time.

The Work:

  • Connect the raw data and transform it
  • Create a relational data model.
  • Create new DAX measures and calculated columns.
  • Create an interactive data analysis report.


  • From 9:00 a.m. to 11:00 a.m., there is very little demand.
  • To cut operating costs, shift operating hours from 11:00 a.m. to 11:00 p.m.
  • Peak hours are from 11:00 AM to 1:00 PM during lunchtime. Demand is highest before dinner, between 4:00 and 6:00 PM.
  • Consider the following options for increasing table turnover and decreasing customer wait for time Increase seating capacity by rearranging the restaurant's layout to make better use of available space and accommodate more tables and seats.
  • Implement a reservation system to better manage customer flow and ensure tables are available even during peak hours.
  • Use targeted marketing campaigns or discounts/special offers to promote off-peak hours.
  • Expanding the business by offering takeout or delivery services for those who want to enjoy the food without having to wait in long lines during peak hours.
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