Data Cleansing tool icon

Data Cleansing Tool

Last modified: September 09, 2021

Docs are available before the release of Designer Cloud so you can get a sneak peek. This content might change between now and the official release.

One Tool Example

Data Cleansing has a One Tool Example. Go to Sample Workflows to learn how to access this and many other examples directly in Alteryx Designer Cloud.

Use Data Cleansing to fix common data quality issues. You can replace null values, remove punctuation, modify capitalization, and more.

Known Limitations

The Data Cleansing tool is not dynamic. If used in a dynamic setting—for example, in a macro intended to work with newly generated column names—the tool doesn't interact with the columns, even if all options are selected. Consider replacing the Data Cleansing tool with a Multi-Field Formula tool.

Numbers with more than 15 digits need to be treated as strings, or they lose precision. Set the column type to a string with the Select tool.

Tool Components


The Data Cleansing tool has 2 anchors.

  • Input anchor: Use the input anchor to connect the data you want to cleanse.
  • Output anchor: The output anchor outputs the cleansed data.

Configure the Tool

Use the Options tab to determine how data quality issues are managed.

 Remove Null Data

Use these options to remove entire rows and columns of null data:

  • Remove Null Rows
    • Remove all rows with a null value in every column.
    • Remove rows with null values—doesn't remove rows with empty string values.
    • Only remove rows that have a null value in every column.
    • A message displays in the Results window with the number of rows that were removed.
  • Remove Null Columns
    • Removes all columns with a null value in every row.
    • Removes columns with null values—does not remove columns with empty string values.
    • Only removes columns that have a null value in every row.
    • A message displays in the Results window with the number of columns that were removed.

Select Fields to Cleanse

Check the columns to cleanse. Check Check All to select all columns and uncheck to deselect all columns.

String Data Types

All options, except for Replace Nulls with 0, apply to string data types. To specify different options for different columns, use multiple Data Cleansing tools in your workflow.

Replace Nulls

  • Replace with Blanks (String Columns): Replace null values with a blank string value. A blank registers as " " rather than [Null]. This option is selected by default.
  • Replace with 0 (Numeric Columns): Replace null values with a 0 (zero). This option is selected by default.

Remove Unwanted Characters

  • Leading and Trailing Whitespace: Removes leading and trailing whitespace. This option is selected by default.
  • Tabs, Line Breaks, and Duplicate Whitespace: Replaces any occurrence of whitespace with a single space, including line endings, tabs, multiple spaces, and other consecutive whitespaces.
  • All Whitespace: Removes any occurrence of whitespace.
  • Letters: Removes all letters, including non-Latin alphabet letters like A b Z À é ö.
  • Numbers: Removes all numbers.
  • Punctuation: Removes the following characters: ! " # $ % & ' ( ) * + , \ - . / : ; < = > ? @ [ / ] ^ _ ` { | } ~

Modify Case

Select Modify Case and then choose an option from the dropdown to change the capitalization of string data types:

  • Upper Case: Capitalize all letters in a string.
  • Lower Case: Convert all letters in a string to lowercase.
  • Title Case: Capitalize the 1st letter of all words in a string.
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