Card and multi-row card in Power BI - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ visualization

intermediate

Identify the correct use of a Card visual

You want to show the total sales amount as a single number on your Power BI report. Which visual should you use?

A Use a Card visual to display the total sales measure.

B Use a Multi-row Card visual to display the total sales measure.

C Use a Table visual to display the total sales measure.

D Use a Matrix visual to display the total sales measure.

💡 Hint

Think about which visual shows a single number clearly.

A Card visual is designed to show one single value, such as total sales, clearly and prominently. Multi-row Card shows multiple values, and Table or Matrix show detailed data.

❓ dax_lod_result

intermediate

Calculate total sales for a specific product category

Given the following DAX measure, what is the output if the current filter context is for the 'Bikes' category only?

Sales Bikes = CALCULATE(SUM(Sales[Amount]), Products[Category] = "Bikes")

Power BI

Sales Bikes = CALCULATE(SUM(Sales[Amount]), Products[Category] = "Bikes")

A Sum of sales amount only for 'Bikes' category in the current filter context.

B Sum of sales amount for all categories ignoring filters.

C Syntax error in the DAX expression.

D Sum of sales amount for 'Bikes' category ignoring current filters.

💡 Hint

CALCULATE changes filter context to the specified condition.

The CALCULATE function applies the filter Products[Category] = "Bikes" on top of the current filter context, so it sums sales only for Bikes category within the current filters.

🔧 Formula Fix

advanced

Why does the Multi-row Card show repeated values?

You created a Multi-row Card visual with the fields: Customer Name and Total Sales. But the visual shows repeated customer names with the same sales amount multiple times. What is the most likely cause?

A The measure Total Sales is not aggregated properly causing repeats.

B The Multi-row Card visual cannot show multiple fields together.

C The data model has duplicate rows for customers causing repeated values.

D The visual needs a slicer to filter unique customers.

💡 Hint

Think about what causes repeated rows in visuals.

If the data model contains duplicate rows for customers, the Multi-row Card will show repeated customer names with their sales. The visual can show multiple fields, and measures aggregate correctly by default.

🎯 Scenario

advanced

Best visual choice for showing multiple KPIs per customer

You want to display for each customer their total sales, total orders, and average order value in a single visual. Which visual is best suited for this in Power BI?

A Use a Pie Chart visual to show the three KPIs per customer.

B Use a Multi-row Card visual with the three measures and Customer Name field.

C Use a Line Chart visual to show the KPIs over time.

D Use a Card visual with all three measures combined into one measure.

💡 Hint

Think about which visual can show multiple values per category clearly.

The Multi-row Card visual can display multiple measures side by side for each category (customer). Card shows only one value, Pie and Line charts are for different purposes.

🧠 Conceptual

expert

Understanding filter context in Card vs Multi-row Card visuals

Which statement best explains how filter context affects Card and Multi-row Card visuals differently in Power BI?

A Multi-row Card visual cannot be filtered by slicers or report filters.

B Both Card and Multi-row Card visuals ignore filter context and show all data.

C Card visual applies filter context per row; Multi-row Card aggregates all data ignoring filters.

D Card visual shows a single aggregated value affected by filter context; Multi-row Card shows multiple rows each affected by filter context individually.

💡 Hint

Consider how each visual displays data and how filters apply.

The Card visual shows one aggregated value that changes with filter context. The Multi-row Card shows multiple rows, each filtered and aggregated according to the current filter context.