Splitting and merging columns in Power BI - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ dax_lod_result

intermediate

Calculate the number of unique customers after splitting a full name column

You have a table with a column FullName containing first and last names separated by a space (e.g., "John Smith"). You split this column into FirstName and LastName. Then you want to count unique customers by LastName.

Which DAX measure correctly counts unique last names?

Power BI

UniqueLastNames = DISTINCTCOUNT('Customers'[LastName])

A UniqueLastNames = COUNT('Customers'[LastName])

B UniqueLastNames = COUNTROWS(VALUES('Customers'[FullName]))

C UniqueLastNames = DISTINCTCOUNT('Customers'[LastName])

D UniqueLastNames = DISTINCTCOUNT('Customers'[FirstName])

💡 Hint

Think about which column contains the last names after splitting.

After splitting, the LastName column holds last names. Using DISTINCTCOUNT on it counts unique last names correctly. Option C counts unique full names, not last names. Option C counts all rows, not distinct. Option C counts unique first names, not last names.

❓ visualization

intermediate

Best visualization to show merged city and state data

You merged two columns City and State into one column Location (e.g., "Seattle, WA"). You want to show sales by location on a report.

Which visualization type is best to clearly show sales by each location?

A A line chart showing sales trend over time by Location

B A pie chart showing sales percentage by Location

C A scatter plot with Location on X axis and sales on Y axis

D A bar chart with Location on the axis and sales as values

💡 Hint

Think about which chart clearly compares sales amounts by categories.

A bar chart is best to compare sales amounts by each location category. Pie charts are less clear with many categories. Line charts show trends over time, which is not the goal here. Scatter plots are for numeric relationships, not categories.

❓ data_modeling

advanced

Handling merged columns for filtering in Power BI

You merged ProductCategory and ProductSubcategory into a single column CategoryFull with format "Category - Subcategory". You want to enable filtering by either category or subcategory in reports.

What is the best data modeling approach to support filtering by both parts?

A Keep only the merged column and use text filters on it

B Keep original separate columns and create the merged column as a calculated column

C Remove original columns and split the merged column back when filtering

D Create a disconnected table with all unique merged values for filtering

💡 Hint

Think about how to keep flexibility for filtering on both category and subcategory.

Keeping original columns and creating a merged calculated column allows filtering by category or subcategory independently, while also showing the merged value. Option B loses filtering flexibility. Option B is inefficient and error-prone. Option B complicates filtering without clear benefit.

🔧 Formula Fix

advanced

Identify the error in this DAX formula for splitting a column

You want to extract the first word from a FullName column using this DAX formula:

FirstName = LEFT('Table'[FullName], FIND(" ", 'Table'[FullName]))

What error will this formula cause?

A It returns an error when there is no space in FullName

B It causes a syntax error due to missing comma

C It returns the first name with an extra space at the end

D It returns the full name without splitting

💡 Hint

Consider what happens if FIND does not find a space.

If FullName has no space, FIND(" ", 'Table'[FullName]) returns an error, causing the whole formula to error. Option A is incorrect because the formula includes the space. Option A is wrong; syntax is correct. Option A is wrong; it does not return full name.

🧠 Conceptual

expert

Best practice for merging columns with different data types

You want to merge a Date column and a Text column into one combined column in Power BI. What is the best practice to avoid errors and maintain data quality?

A Convert the Date column to text format before merging

B Merge columns directly without conversion; Power BI handles types automatically

C Convert the Text column to date format before merging

D Create a new numeric column representing date as a number and merge with text

💡 Hint

Think about how Power BI treats different data types when merging columns.

To merge columns with different data types, convert the Date column to text first. This avoids errors and ensures the merged column is consistent text. Option A can cause errors or unexpected results. Option A is invalid if text is not a date. Option A complicates the model unnecessarily.