✏️ Text Cleansing
Apply string transformations to clean up text fields across all or selected columns.
Remove Leading Spaces
Strips whitespace from the start of cell values
Apply to columns
Remove Trailing Spaces
Strips whitespace from the end of cell values
Apply to columns
Remove Extra / Double Spaces
Collapses multiple consecutive spaces into one
Apply to columns
Case Conversion
Convert text to UPPER, lower or Title Case
Convert to
Apply to columns
Remove Special Characters
Strip unwanted symbols, control chars or custom patterns
Remove
Apply to columns
Fill Blank Cells
Replace empty / null cells with a default value
Fill text cols with
Fill numeric cols with
Apply to columns
📅 Date & Time Formatting
Standardize date columns to a consistent output format.
Normalize Date Format
Convert all date values to a standard output format
Output date format
Apply to columns
🗓️ Period Formats
Add or reformat Quarter, Month, and Year columns derived from date fields.
Quarter Format
Derive or standardize quarter values
Source column
Quarter format
Output column name
Month Format
Derive or standardize month values
Source column
Month format
Output column name
Year Format
Derive or standardize year values
Source column
Year format
Output column name
🔢 Number Formatting
Clean and standardize numeric values across columns.
Clean Numbers
Remove currency symbols, commas; convert text-numbers to numeric
Remove currency symbol
Decimal places
Apply to columns
Cap / Floor Values (Min-Max)
Clamp numeric values within a defined range
Minimum value
Maximum value
Apply to columns
✅ Data Validation
Flag or remove invalid records. Results shown in preview.
Email Validation
Flag cells that are not valid email addresses
Email column(s)
On invalid
Phone Number Standardization
Normalize phone numbers to a consistent format
Phone column(s)
Output format
Standardize Boolean / Flag Values
Convert Yes/No, y/n, 1/0, TRUE/FALSE to a uniform format
Output format
Apply to columns
🔴 Mandatory Columns
Select which columns must not be empty. Rows with missing values will be flagged.
Required / Mandatory Fields
Flag or remove rows where selected columns are empty
On violation
📈 Greater Than Zero
Validate that numeric values in selected columns are positive (> 0).
Positive Value Enforcement
Flag rows where column value is zero, negative or blank
On violation
🔁 Duplicate Detection
Find and remove or flag duplicate rows.
Remove / Flag Duplicates
Based on all columns or a key-column subset
Detect duplicates on
On duplicate
🔍 Find & Replace
Bulk text substitution across selected columns. Add multiple rules.
Find & Replace Rules
Multiple search-replace pairs, with optional regex
Apply to columns
⚙️ Advanced Options
Additional cleansing operations for power users.
Remove Blank Rows
Delete rows where all cells are empty
Row is blank if
Strip HTML Tags
Remove <b>, <span> and other HTML markup from text
Apply to columns
Add Row Index Column
Prepend a sequential row number column to the output
Column name
Start from
Pad / Zero-fill Codes
Ensure PIN codes, account numbers or IDs have fixed length
Target length
Pad character
Apply to columns
Add Cleanse Status Column
Append a column showing PASS / FAIL / WARN for each row
Column name