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SUPER STORE SALES DASHBOARD

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The dataset was scrapped from kaggle. 

This analysis was undertaken by Walter Boat, Lead Data Analyst at Data Driven Consult.


Purpose

  • The purpose of this analysis is to  determine the top selling product categories of the business.
  •  The analysis is to determine the percentage of revenue that resulted in profit. 
  • The company wants to find out the geographical location of their customers in order to determine where to invest their advertising budget. 
  • The profit trend over the 4 years period was another paramount insight needed by the company to forecast future revenue.

Getting the dataset

This dataset was scrapped from kaggle.com in csv format. 

Cleaning the data

Data cleaning was done using Microsoft Power Query. The data was moderately clean for analysis except for some few fields that do not affect the analysis. Fields such as customer name, customer ID and product ID were deleted. A new field (Year) was created from the order date to extract only the year from the order date.

Creating the Visuals

The data visualization was created using Microsoft Power BI.

Insights

  • Overall Sales is currently at 9476278.88. Sales for Country United States and other segments are significantly higher than others.
  • Overall Profit is currently at 1089913.14. 4 segments have significantly lower Profit than others, and 16 segments have significantly higher Profit.
  • Consumer products constitute 51% of company`s sales.
  • Quantity sold in the Africa region is encouraging but large shipping costs depleted the net profit from this region.
  • Only 11% of revenue resulted in profit due to high shipping costs. 


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