CSV and text file import 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 analyze last quarter's sales data which is stored in CSV and text files. You need to import these files into Power BI to create reports.

📊 Data: You have two files: 'SalesData.csv' containing sales transactions with columns Date, Product, Region, and SalesAmount; and 'ProductInfo.txt' containing product details with columns ProductID, ProductName, and Category separated by tabs.

🎯 Deliverable: Import both files into Power BI, combine the data properly, and prepare it for creating sales reports.

Sample Data

Date	Product	Region	SalesAmount
2024-01-05	P1001	North	250
2024-01-06	P1002	South	180
2024-01-07	P1003	East	300
2024-01-08	P1001	West	220
2024-01-09	P1002	North	190
2024-01-10	P1003	South	310
2024-01-11	P1001	East	260
2024-01-12	P1002	West	200

ProductID	ProductName	Category
P1001	Wireless Mouse	Accessories
P1002	USB Keyboard	Accessories
P1003	HD Monitor	Displays

1

Step 1: Open Power BI Desktop and start a new report.

No formula needed.

Expected Result

Power BI Desktop is ready for data import.

2

Step 2: Import the 'SalesData.csv' file.

Home tab > Get Data > Text/CSV > Select 'SalesData.csv' > Load

Expected Result

SalesData table is loaded with columns Date, Product, Region, SalesAmount.

3

Step 3: Import the 'ProductInfo.txt' file with tab delimiter.

Home tab > Get Data > Text/CSV > Select 'ProductInfo.txt' > In preview, set delimiter to Tab > Load

Expected Result

ProductInfo table is loaded with columns ProductID, ProductName, Category.

4

Step 4: Check data types for both tables and correct if needed.

In Power Query Editor, verify Date is date type, SalesAmount is number, ProductID and Product are text.

Expected Result

Data types are correct for analysis.

5

Step 5: Create a relationship between SalesData and ProductInfo tables on Product and ProductID columns.

Model view > Drag 'Product' from SalesData to 'ProductID' in ProductInfo

Expected Result

Relationship is active and many-to-one from SalesData to ProductInfo.

6

Step 6: Close Power Query Editor and apply changes.

Click 'Close & Apply' button

Expected Result

Data is loaded into Power BI model ready for report building.

Final Result

-----------------------------------------
| Sales Report Dashboard                 |
|---------------------------------------|
| Region | Total Sales | Top Product    |
|---------------------------------------|
| North  | $440        | Wireless Mouse |
| South  | $490        | HD Monitor     |
| East   | $560        | HD Monitor     |
| West   | $420        | Wireless Mouse |
-----------------------------------------

✓East region has the highest total sales.

✓HD Monitor is the top-selling product in South and East regions.

✓Wireless Mouse leads sales in North region.

✓Wireless Mouse leads sales in West region.

Bonus Challenge

Create a calculated column in SalesData to categorize sales as 'High' if SalesAmount > 250, else 'Low'.

Show Hint

Use Power Query Editor or DAX formula: SalesCategory = IF(SalesData[SalesAmount] > 250, "High", "Low")

Practice

1. What is the primary purpose of importing CSV or text files into Power BI?

easy

A. To export Power BI reports to CSV format

B. To create visualizations without any data

C. To bring external data into Power BI for analysis

D. To write DAX formulas automatically

Solution

1. Step 1: Understand the role of CSV/text import

   CSV and text file import allows users to bring external data into Power BI.

2. Step 2: Identify the main use of imported data

   Imported data is used for analysis and creating reports in Power BI.

3. Final Answer:

   To bring external data into Power BI for analysis -> Option C

4. Quick Check:

   Importing data = Bringing external data in [OK]

Hint: Import means bringing data inside Power BI [OK]

Common Mistakes:

• Confusing import with export
• Thinking import creates visuals automatically
• Assuming import writes formulas

2. Which of the following is the correct way to start importing a CSV file in Power BI Desktop?

easy

A. Click 'Get Data' > 'CSV' and select the file

B. Write a DAX formula to load the CSV

C. Use the 'New Measure' button to import CSV

D. Drag and drop the CSV file into the report canvas

Solution

1. Step 1: Locate the import option in Power BI Desktop

   The correct method is to use the 'Get Data' button and choose 'CSV' to import files.

2. Step 2: Confirm the import process

   After selecting the CSV file, Power BI loads it into the data model or Power Query Editor.

3. Final Answer:

   Click 'Get Data' > 'CSV' and select the file -> Option A

4. Quick Check:

   Get Data > CSV = Correct import method [OK]

Hint: Use 'Get Data' menu to import files [OK]

Common Mistakes:

• Trying to import CSV via DAX formulas
• Using 'New Measure' which is for calculations
• Dragging files onto report canvas doesn't import

3. After importing a CSV file with columns 'Date', 'Sales', and 'Region', which Power Query step will correctly change the 'Date' column to date type?

medium

A. Table.AddColumn(Source, "Date", each DateTime.LocalNow())

B. Table.RenameColumns(Source, {{"Date", type date}})

C. Table.RemoveColumns(Source, {"Date"})

D. Table.TransformColumnTypes(Source, {{"Date", type date}})

Solution

1. Step 1: Identify the function to change column type

   Table.TransformColumnTypes changes the data type of specified columns.

2. Step 2: Confirm correct syntax for changing 'Date' column to date type

   The syntax Table.TransformColumnTypes(Source, {{"Date", type date}}) correctly changes 'Date' column type.

3. Final Answer:

   Table.TransformColumnTypes(Source, {{"Date", type date}}) -> Option D

4. Quick Check:

   TransformColumnTypes changes data type [OK]

Hint: Use TransformColumnTypes to set column data types [OK]

Common Mistakes:

• Using RenameColumns instead of TransformColumnTypes
• Removing the column instead of changing type
• Adding a new column instead of modifying existing

4. You imported a CSV file but the data preview shows all columns as 'Any' type and some dates are text. What is the best way to fix this in Power Query?

medium

A. Write a DAX measure to convert text to date

B. Manually change column types using 'Transform' > 'Data Type' menu

C. Delete the query and re-import the file

D. Ignore the issue and load data as is

Solution

1. Step 1: Identify how to fix incorrect data types in Power Query

   Power Query allows manual data type changes via the 'Transform' tab.

2. Step 2: Apply manual data type change to fix text dates

   Changing the column type to 'Date' converts text dates properly before loading.

3. Final Answer:

   Manually change column types using 'Transform' > 'Data Type' menu -> Option B

4. Quick Check:

   Manual type change fixes data type issues [OK]

Hint: Use Transform tab to fix column types before loading [OK]

Common Mistakes:

• Deleting query wastes work done
• Using DAX measure instead of fixing source data
• Ignoring data type issues causes errors later

5. You have multiple CSV files with the same structure in a folder. How can you efficiently import and combine them in Power BI?

hard

A. Use 'Get Data' > 'Folder', select the folder, then combine files in Power Query

B. Import each CSV file separately and merge tables manually in report view

C. Write a DAX formula to union all CSV files after import

D. Copy and paste CSV content into Power BI manually for each file

Solution

1. Step 1: Identify the best method to import multiple CSV files

   Power BI's 'Get Data' > 'Folder' option allows importing all files in a folder at once.

2. Step 2: Use Power Query's combine files feature

   After selecting the folder, Power Query can automatically combine files with the same structure.

3. Final Answer:

   Use 'Get Data' > 'Folder', select the folder, then combine files in Power Query -> Option A

4. Quick Check:

   Folder import + combine = efficient multi-file import [OK]

Hint: Use Folder import to combine many CSVs at once [OK]

Common Mistakes:

• Importing files one by one wastes time
• Trying to union files with DAX which is not for import
• Copy-pasting data is error-prone and slow