Data type changes in Power BI - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ dax_lod_result

intermediate

DAX Measure Output After Data Type Change

You have a column 'SalesAmount' stored as text. You create this DAX measure:

Total Sales = SUM('Sales'[SalesAmount])

What will be the result when you use this measure in a report?

Power BI

Total Sales = SUM('Sales'[SalesAmount])

A An error because SUM cannot aggregate text values

B The sum of all sales amounts converted automatically from text to number

C Zero, because text values are ignored in SUM aggregation

D The count of rows in the Sales table

💡 Hint

SUM requires numeric data types, text cannot be summed directly.

SUM function in DAX only works on numeric columns. If the column is text, it causes an error.

❓ visualization

intermediate

Effect of Changing Data Type on Visualization

You have a date column stored as text in Power BI. You change its data type to Date. What is the most likely effect on a line chart using this column on the axis?

A The line chart will correctly order points by date

B The line chart will fail to render due to incompatible data type

C The line chart will show points in alphabetical order of the date text

D The line chart will aggregate all points into one

💡 Hint

Dates as text sort alphabetically, dates as Date type sort chronologically.

Changing the column to Date type allows Power BI to order the axis chronologically, improving the line chart.

❓ data_modeling

advanced

Data Type Impact on Relationships

You have two tables: 'Orders' with 'OrderDate' as text, and 'Calendar' with 'Date' as Date type. You create a relationship between 'Orders[OrderDate]' and 'Calendar[Date]'. What will happen?

A Power BI will automatically convert text to Date and create the relationship

B The relationship will be created and work correctly

C The relationship will be created but cause incorrect filtering

D The relationship will not be created because data types do not match

💡 Hint

Relationships require matching data types on both sides.

Power BI requires both columns in a relationship to have the same data type. Text and Date types cannot be related directly.

🔧 Formula Fix

advanced

Fixing a Data Type Conversion Error in Power Query

You try to change a column 'Price' from text to decimal number in Power Query but get an error on some rows. What is the most likely cause?

A The column is already decimal number type

B Some rows contain non-numeric text like 'N/A' or empty strings

C Power Query does not support decimal numbers

D The data source is offline

💡 Hint

Non-numeric text cannot convert to numbers.

If text contains values that cannot be converted to numbers, Power Query throws an error during type change.

🧠 Conceptual

expert

Choosing Data Types for Performance and Accuracy

In a large sales dataset, which data type choice for the 'Quantity' column is best for balancing performance and accuracy?

A Date type to track quantity changes over time

B Decimal Number type to allow fractional quantities

C Whole Number type because quantities are always integers

D Text type to avoid conversion errors

💡 Hint

Think about the nature of quantity and data size impact.

Whole Number type uses less memory and is accurate for integer quantities, improving performance.

Practice

1. Why is it important to change data types correctly in Power BI?

easy

A. Because it speeds up the internet connection

B. Because it changes the color of the visuals automatically

C. Because it deletes duplicate rows in the dataset

D. Because it helps Power BI understand and process data accurately

Solution

1. Step 1: Understand the role of data types in Power BI

   Data types tell Power BI how to treat each column, like numbers or text.

2. Step 2: Recognize the impact of correct data types

   Correct types ensure calculations and visuals work properly without errors.

3. Final Answer:

   Because it helps Power BI understand and process data accurately -> Option D

4. Quick Check:

   Correct data types = Accurate processing [OK]

Hint: Data types guide Power BI how to handle data [OK]

Common Mistakes:

• Thinking data types change visual colors
• Believing data types remove duplicates
• Assuming data types affect internet speed

2. Which of the following is the correct way to change a column's data type to Whole Number in Power Query Editor?

easy

A. Right-click the column header, select 'Change Type' > 'Whole Number'

B. Double-click the column header and type 'Whole Number'

C. Click 'Home' tab and press 'Delete' key

D. Drag the column to the 'Values' area

Solution

1. Step 1: Recall how to change data types in Power Query Editor

   Right-clicking the column header opens a menu with 'Change Type' options.

2. Step 2: Identify the correct option for Whole Number

   Selecting 'Whole Number' under 'Change Type' sets the column data type correctly.

3. Final Answer:

   Right-click the column header, select 'Change Type' > 'Whole Number' -> Option A

4. Quick Check:

   Right-click > Change Type > Whole Number [OK]

Hint: Use right-click menu to change data types quickly [OK]

Common Mistakes:

• Trying to type data type directly in header
• Pressing Delete key removes data, not changes type
• Dragging columns changes layout, not data type

3. Given a column 'Sales' with text data type containing values like '100', '200', '300', what will be the result of this DAX measure after changing 'Sales' to Whole Number type?

Total Sales = SUM('Table'[Sales])

medium

A. It will return an error because SUM cannot be used on numbers

B. It will concatenate the text values: '100200300'

C. It will sum the numbers correctly: 600

D. It will return zero because the column is text

Solution

1. Step 1: Understand the effect of changing 'Sales' to Whole Number

   Changing 'Sales' from text to whole number converts values like '100' to 100 as numbers.

2. Step 2: Evaluate the SUM function on numeric data

   SUM adds numeric values, so 100 + 200 + 300 = 600.

3. Final Answer:

   It will sum the numbers correctly: 600 -> Option C

4. Quick Check:

   SUM of numbers = 600 [OK]

Hint: SUM works only on numeric data types [OK]

Common Mistakes:

• Expecting SUM to concatenate text
• Thinking SUM causes error on numbers
• Assuming text columns sum to zero

4. You changed a date column's data type to Text in Power Query, but your visuals show incorrect dates. What is the likely problem?

medium

A. Text data type improves date calculations automatically

B. Changing date to text breaks date calculations and sorting

C. Power BI ignores data types in visuals

D. You must refresh the data source to fix visuals

Solution

1. Step 1: Analyze the impact of changing date to text

   Changing a date column to text removes date properties, so calculations and sorting fail.

2. Step 2: Understand why visuals show incorrect dates

   Without date type, Power BI cannot interpret or order dates properly in visuals.

3. Final Answer:

   Changing date to text breaks date calculations and sorting -> Option B

4. Quick Check:

   Date as text breaks date logic [OK]

Hint: Keep date columns as Date type for correct visuals [OK]

Common Mistakes:

• Assuming text type improves date calculations
• Believing Power BI ignores data types in visuals
• Thinking refresh fixes data type issues

5. You have a column 'Price' imported as Text with values like '12.50', '15.00', and '9.99'. You want to calculate the total price in a measure. Which steps correctly fix the data type and calculate the total?

hard

A. Change 'Price' to Decimal Number in Power Query, then use Total Price = SUM('Table'[Price])

B. Keep 'Price' as Text and use Total Price = CONCATENATE('Table'[Price])

C. Change 'Price' to Whole Number and use Total Price = SUM('Table'[Price])

D. Change 'Price' to Date and use Total Price = SUM('Table'[Price])

Solution

1. Step 1: Identify correct data type for decimal prices

   Prices with decimals require Decimal Number type, not Whole Number or Text.

2. Step 2: Use SUM on Decimal Number column

   SUM works on numeric types, so after changing type, Total Price = SUM('Table'[Price]) calculates total correctly.

3. Final Answer:

   Change 'Price' to Decimal Number in Power Query, then use Total Price = SUM('Table'[Price]) -> Option A

4. Quick Check:

   Decimal type + SUM = correct total [OK]

Hint: Use Decimal Number for prices with decimals [OK]

Common Mistakes:

• Using Whole Number loses decimals
• Concatenating text instead of summing
• Changing price to Date type causes errors