The Transform Tab is for modifying data within your existing columns. Unlike the "Add Column" tab, it cleans the data "in-place," keeping your table lean and efficient.
? Key Concepts
Overwrites current column data
Keeps column count the same
Every action creates an Applied Step
? Main Groups
Format: Trim (removes spaces), Clean (removes non-printable chars), Case changes.
Extract: Pulls text based on length or delimiters (like @ in emails).
Number Column: Mathematical operations and rounding.
? Use Cases
Fixing messy Excel names with leading/trailing spaces.
Extracting usernames from email addresses.
Converting mixed-case city names to standard UPPERCASE.
Cleaning non-printable characters from web-scraped data.
? Text Transformation Lab
Try these standard Transform functions on the "messy" sample data below:
Original / Messy Data
Transformed Result
Rahul
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anita@gmail.com
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✅ Tips & Best Practices
Trim vs. Clean: Always use Trim for visible spaces and Clean for invisible system characters.
Perform Early: Do these transformations in Power Query rather than using DAX calculated columns to save memory.
Step Naming: Rename the auto-generated "Trimmed Text" step to "Removed Spaces from Name" for better documentation.
Check Nulls: Transformations on null values remain null; check your data quality before applying extracts.
? Try It Yourself
Import the Customer CSV and select the CustomerName column.
Go to the Transform Tab → Format and click Trim.
Select the Email column → Extract → Text Before Delimiter and enter @.