Pizza Sales Dashboard

Pizza Sales Dashboard

Dashboard Link:

View Dashboard

SQL Link:

View SQL Script

Our company is focused on pizza sales, and to effectively track and analyze our performance, we need a comprehensive Pizza Sales Dashboard in Power BI.

Objective:

Design and develop a dynamic, interactive Pizza Sales Dashboard that visualizes critical KPIs related to pizza sales. The dashboard will help us understand our sales performance over time and make data-driven decisions.

Problem Statement:

The dashboard should provide real-time insights into key performance indicators for our pizza sales data. This will enable informed decisions, monitor progress, and identify trends and growth opportunities.

Key Sales Metrics:

  • Total Revenue: Sum of all pizza order prices.
  • Average Order Value: Average spend per order.
  • Total Pizzas Sold: Total quantity of pizzas sold.
  • Total Orders: Total number of orders placed.
  • Average Pizzas Per Order: Average number of pizzas per order.

Chart Requirements:

  • Weekly Trend for Total Orders:

    Bar chart illustrating weekly total order trends. Highlighted the day with the most sales using conditional formatting.

  • Monthly Trend for Total Orders:

    Line chart showing total orders by month with markers for clear identification of trends.

  • Percentage of Sales by Pizza Category:

    Pie chart displaying sales distribution across pizza categories.

  • Percentage of Sales by Pizza Size:

    Pie chart representing sales distribution by pizza size.

  • Total Pizzas Sold by Pizza Category:

    Funnel chart showing pizzas sold per category.

  • Top 5 Best Sellers by Revenue, Quantity, and Orders:

    Bar chart highlighting the top 5 best-selling pizzas. Used conditional formatting for emphasis.

  • Bottom 5 Worst Sellers by Revenue, Quantity, and Orders:

    Bar chart showcasing the bottom 5 worst-selling pizzas with conditional formatting.

Steps Followed:

  1. Data Quality Check / Data Cleaning:
    • Load Data: Imported the dataset from SQL Server into Power BI Desktop.
      SQL Server
    • Data Quality Check: Used Power Query Editor to remove null values and filter rows.
      Data Preview
    • Replace Values: Standardized data in the 'pizza_size' column using Power Query.
      Replace Value
  2. Enhanced Data Visualization with DAX:
    • Create Day of the Week Column: Used Power Query’s Add Column to extract the day name from the order date.
      Creating Date Name
  3. DAX Calculations:
    • Created a column for month ordering: 
      Month Order = MONTH(pizza_sales[order_date])
    • Shortened day and month names: 
      Order Day = UPPER(LEFT(pizza_sales[Day Name], 3))
Order Month = UPPER(LEFT(pizza_sales[Month Name], 3))
    • Created custom day names using DAX: 
      Week Day = FORMAT(pizza_sales[order_date], "DDDD")
    • Ordered weekdays numerically: 
      Week Order = WEEKDAY(pizza_sales[order_date])
  4. KPIs and Measures:
    • Total Revenue: 
      Total Revenue = SUM(pizza_sales[total_price])

      Total Revenue
    • Average Order Value: 
      Average Order Value = [Total Revenue] / [Total Orders]

      Average Order Value
    • Total Pizzas Sold: 
      Total Pizzas Sold = SUM(pizza_sales[quantity])

      Total Pizzas Sold
    • Total Orders: 
      Total Orders = DISTINCTCOUNT(pizza_sales[order_id])

      Total Orders
    • Average Pizzas Per Order: 
      Average Pizzas Per Order = [Total Pizzas Sold] / [Total Orders]

      Average Pizzas Per Order
  5. Chart Requirements:
    • Weekly Trend for Total Orders:

      We created a bar chart that showed the weekly total order trend. Conditional formatting was used to highlight the day with the highest sales.
      Daily Trend

    • Monthly Trend for Total Orders:

      A line chart was created to illustrate total orders by month. Background and data markers were added for clarity.
      Area Chart

    • Percentage of Sales by Pizza Category:

      We generated a pie chart to display the distribution of sales across pizza categories.
      Sales by Pizza Category

    • Percentage of Sales by Pizza Size:

      A pie chart was created to represent the percentage of sales by pizza size.
      Sales by Pizza Size

    • Total Pizzas Sold by Pizza Category:

      A funnel chart was created to present the total number of pizzas sold for each pizza category.
      Total Pizzas Sold by Category

    • Top 5/Bottom 5 Best Sellers by Revenue, Total Quantity, and Total Orders:

      A bar chart was created to highlight the top and bottom 5 selling pizzas based on Revenue, Total Quantity, and Total Orders. Conditional formatting was used to effectively visualize the data.
      Top Bottom 5

  6. Creating Sliders:
    • Category Slider: A category slider was created for the dashboard to allow dynamic, real-time changes for analysis based on category.
      Category Slicer
    • Date Slider: A date slider was created to enable data filtering in real-time, allowing for alternative analysis.
      Date Slicer
  7. Creating Navigation Buttons:

    Implemented "Home" and "Best/Worst Seller" buttons to enable navigation between different pages.
    Navigational Buttons

Snapshot of Dashboard (Power BI Desktop):

Overview:

Dashboard Overview

Details:

Dashboard Details

Insights:

  • Busiest Day: Friday had the highest number of pizza orders, with 3,500 total orders.
  • Busiest Month: July saw the most orders, with 1,935 orders, showing a gradual increase from February to July.
  • Pizza Category Insights: Classic Pizzas made up 26.91% of total sales, followed by Supreme (25.46%) and Chicken (23.96%).
  • Pizza Size Breakdown: Large pizzas dominated sales, followed by Medium (30.49%).

Top Performers:

  • Top Pizza by Revenue: Thai Chicken Pizza - $43,000
  • Top Pizza by Quantity: Classic Deluxe - 2,500 pizzas
  • Top Pizza by Total Orders: Classic Deluxe - 2,300 orders

Bottom Performers:

  • Bottom Pizza by Revenue: Brie Carre - $12,000
  • Bottom Pizza by Quantity: Brie Carre - 490 pizzas
  • Bottom Pizza by Total Orders: Brie Carre - 480 orders