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The report provides insights into pizza sales trends for 2015, focusing on peak periods, customer preferences for large pizzas, and the best-performing menu items.

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kshitiz1302/Pizza-Sales-Report

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Pizza Sales Report Dashboard

Problem Statement

This report analyzes pizza sales data from January to December 2015, generating $817.86K in total revenue from 21,350 orders and 49,574 pizzas sold.

It highlights key trends such as peak sales on Friday and Saturday evenings, large pizzas dominating with 45.89% of sales, and the Thai Chicken Pizza leading in revenue at $43K.

The findings aim to guide strategic decisions for enhancing performance and customer satisfaction.

Steps followed

  • Step 1 : Prepare a CSV file for the dataset and create tables in the SQL.

  • Step 2 : Import the CSV file to SQL.

  • Step 3 : Perform some Data-Modeling in SQL through MYSQL and then import the dataset from the SQL Server into Power BI by establishing a direct connection of servers.

  • Step 4 : Open the power query editor. In the view tab under the Data preview section, check the "column distribution," "column quality," and "column profile" options.

  • Step 5 : It was observed that in none of the columns errors & empty values were present

  • Step 6 : In the report view, under the view tab, theme was selected..

  • Step 7 : Visual filters (Slicers) were added for three fields named "Pizza Size", "Order Date" & "Pizza Category".

  • Step 9 : Four card new visuals were added to the canvas, representing Total Revenue, Total Orders, Total Pizza Sold, Average Order value & Average Pizza Per Order. Using visual level filter from the filters pane, basic filtering was used & null values were unselected for consideration into average calculation.

         Although, by default, while calculating average, blank values are ignored.
    
  • Step 10 : Calculated column was created to extract order day from calender.

for creating new column following DAX expression was written;

    order day = UPPER(LEFT(pizza_sales[Day Name],3))

Snap of new calculated column,

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  • Step 11 : Another calculated column was created to extract order month from calender.

for creating new column following DAX expression was written;

    order month = UPPER(LEFT(pizza_sales[Month Name],3))

Snap of new calculated column,

Image

  • Step 12: New measure was created to find total revenue.

Following DAX expression was written for the same,

    Total Revenue = SUM(pizza_sales[total_price])       

A card visual was used to represent total revenue.

Image

  • Step 13 : New measure was created to find total orders,

Following DAX expression was written to find total order placed,

    Total Orders = DISTINCTCOUNT(pizza_sales[order_id])

A card visual was used to represent this value.

Snap of total orders placed by customers

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  • Step 14 : New measure was created to calculate total pizza sold in whole year.

Following DAX expression was written to find pizza sold

     Total Pizza Sold = SUM(pizza_sales[quantity])

A card visual was used to represent this total pizza sold.

Snap of total pizza sold

Image

  • Step 15 : New measure was created to calculate average order value in whole year.

Following DAX expression was written to find this,

     Avg Order Value = [Total Revenue]/[Total Orders]

A card visual was used to represent average order value.

Snap of this measure

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  • Step 16 : New measure was created to calculate average pizza per order.

Following DAX expression was written to find this,

    Avg Pizzas per Order = [Total Pizza Sold]/[Total Orders]

A card visual was used to represent average pizza per order.

Snap of this measure

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Snapshot of Dashboard (Power BI Service)

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Report Snapshot (Power BI DESKTOP)

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Insights

A double page report was created on Power BI Desktop

Following inferences can be drawn from the dashboard;

[1] Total Number of Orders = 21350

Total revenue was $817.86K.

Total Pizza sold 49,570.

The average order value was $38.31.

2.32 pizzas sold per order.

[2] Some other insights

Pizza Category

1.1) Classic pizzas contributed the most sales 26.91% (14,888 units).

1.2) 25.46 % revenue produced by Supreme pizzas (11,987 units).

1.3) 23.96 % revenue produced by Chicken pizzas (11,050 units).

1.4) 23.68 % revenue produced by Veggie pizzas (11,649 units).

     thus, maximum Classic Pizzas are at top in both sales and units sold category.

Pizza Size

2.1) 45.89 % revenue produced by Larged sized pizzas (18,956 units).

2.2) 30.49 % revenue produced by Medium sized pizzas (15,635 units).

2.3) 21.77 % revenue produced by Regular sized pizzas (14,403 units).

2.4) 1.72% revenue produced by X-Large sized pizzas (552 units).

2.5) 0.12% revenue produced by XX-Large sized pizzas(28 units).

     thus, Larged Sized Pizzas top the chart.         

Pizza Name

3.1) The Thai Chicken Pizza generated the highest revenue ($43K), while the Classic Deluxe Pizza had the most orders (2,329).

3.2) The Brie Carre Pizza had the lowest revenue ($12K) and the fewest orders (480).\

Other

Friday and Saturday evenings had the highest sales, with July and January being the peak months.