9. Data Science Series | Creating reports using Power BI

Continuing from where we left in the previous blog, we will generate reports for the model we developed from the dataset. So, after loading the dataset in the Power BI, let’s create reports.

Creating Report in Power BI

This report will be created using various visualizations for different fields, and it will be shown in the reports tab of Power BI.

First, we will be creating a visualization that shows the representation of quantity sold by product key and the product category. For making this visualization, we have to select a category, product_key, the amount from Product, and Sales_Facts table, respectively and choose the visualization from the visualization tab.

Select the related columns

The generated pie chart for selected columns

Data-Flow type representation of the same data

Next, we will create a pie chart representation used to get the sales revenue representation for all the cities present. The chart represents the percentage of sales revenue with the total amount of income for individual towns. To create this visualization, choose sales_revenue and city attributes from Sales_Facts and Store table.

The donut-shaped chart for displaying the sales revenue per city

Detailed report for sales revenue per city

Next, we will generate a report on the STORE. For that purpose, we will create charts that will compare cost per sq. feet, budgeted employees, and retail sq. footage per city. For visualizing the report, select the cost_per_square_foot and city from STORE; similarly, for the second chart, select budgeted_employees and city; select the final chart retail_square_footage and city from the STORE field. It will be displayed like:

Comparison of stores by cities

Now, let’s compare the products based on their original price and the price they were sold. For that, we will select a description from PRODUCT, actual_sales_price, and original_sales_price from SALES_FACTS.

This shows the original price of the laptop and how much it was sold at

Now, we will compare the sold quantity and returned quantity per store. For that, we will use a ribbon graph, and we will use the product_key and returned_quantity from RETURN_FACTS and quantity_sold from SALES_FACTS.

Comparison between sold and returned products at various stores

I hope this blog helps you in understanding the basics of report generation using Power BI.




IT Engineering at Charusat University

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Thakkar Krunal Balkrishna

Thakkar Krunal Balkrishna

IT Engineering at Charusat University

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