Data type changes in Power BI - Real Business Scenario

Scenario Mode

👤 Your Role: You are a sales analyst at a retail company.

📋 Request: Your manager wants you to prepare a sales report but notices some numbers are treated as text, causing errors in calculations. You need to fix the data types to get accurate totals and averages.

📊 Data: You have a sales dataset with columns: OrderID (text), Product (text), Quantity (text), Price (text), and OrderDate (text). Quantity and Price should be numbers, and OrderDate should be a date.

🎯 Deliverable: A Power BI report with correct data types applied, showing total sales amount and average quantity sold per product.

Sample Data

OrderID	Product	Quantity	Price	OrderDate
ORD001	Notebook	10	2.5	2024-01-05
ORD002	Pen	20	1.2	2024-01-06
ORD003	Notebook	5	2.5	2024-01-07
ORD004	Marker	15	3.0	2024-01-08
ORD005	Pen	10	1.2	2024-01-09
ORD006	Notebook	8	2.5	2024-01-10
ORD007	Marker	7	3.0	2024-01-11
ORD008	Pen	12	1.2	2024-01-12

1

Step 1: Open Power BI Desktop and load the sales data table.

Use 'Get Data' to import the data from your source file.

Expected Result

Sales data appears in Power BI with all columns as text type.

2

Step 2: Go to the 'Transform Data' option to open Power Query Editor.

Click 'Transform Data' button on the Home ribbon.

Expected Result

Power Query Editor opens showing the sales data.

3

Step 3: Change the data type of 'Quantity' column from text to whole number.

Select 'Quantity' column, then choose 'Data Type' dropdown and select 'Whole Number'.

Expected Result

'Quantity' column values convert to numbers without errors.

4

Step 4: Change the data type of 'Price' column from text to decimal number.

Select 'Price' column, then choose 'Data Type' dropdown and select 'Decimal Number'.

Expected Result

'Price' column values convert to decimal numbers correctly.

5

Step 5: Change the data type of 'OrderDate' column from text to date.

Select 'OrderDate' column, then choose 'Data Type' dropdown and select 'Date'.

Expected Result

'OrderDate' column values convert to date format.

6

Step 6: Close and apply the changes to load the transformed data into Power BI.

Click 'Close & Apply' button in Power Query Editor.

Expected Result

Data loads with correct data types applied.

7

Step 7: Create a new measure to calculate total sales amount.

Total Sales = SUMX(Sales, Sales[Quantity] * Sales[Price])

Expected Result

Measure 'Total Sales' calculates the sum of Quantity times Price.

8

Step 8: Create a new measure to calculate average quantity sold per product.

Average Quantity = AVERAGE(Sales[Quantity])

Expected Result

Measure 'Average Quantity' calculates the average quantity.

9

Step 9: Build a report visual: add a table with 'Product', 'Total Sales', and 'Average Quantity' columns.

Insert Table visual, drag 'Product' field, then add 'Total Sales' and 'Average Quantity' measures.

Expected Result

Table shows each product with correct total sales and average quantity.

Final Result

-----------------------------------------
| Product  | Total Sales | Average Qty  |
-----------------------------------------
| Notebook | 57.5        | 7.67         |
| Pen      | 50.4        | 14.0         |
| Marker   | 66.0        | 11.0         |
-----------------------------------------

✓Notebook has total sales of 57.5 with an average quantity of about 7.67 units sold.

✓Pen has total sales of 50.4 with an average quantity of 14 units sold.

✓Marker leads in total sales with 66.0 and average quantity of 11 units.

Bonus Challenge

Create a line chart showing total sales over time by month.

Show Hint

Use the 'OrderDate' column (now a date type) to create a month hierarchy and plot 'Total Sales' measure on the Y-axis.

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