How do you identify records with missing values in Alteryx?

Identifying records with missing values in Alteryx is effectively accomplished through the Data Cleansing tool or the Filter tool. The Data Cleansing tool allows you to efficiently remove unwanted characters, fill in missing values, or identify nulls based on specified criteria. This makes it useful for preparing clean, usable datasets by addressing missing values directly within the workflow.

On the other hand, the Filter tool enables you to set conditions to isolate records that meet specific criteria, including those with missing values. By configuring the conditions to check for null or empty fields, you can quickly pinpoint and analyze records that require attention.

Using these tools provides a direct and straightforward mechanism for handling missing data, which is essential for data integrity. The other options, such as merging datasets with the Join tool or exporting to check for blanks, do not directly address the issue of identifying missing values within a dataset context; they serve different purposes in data manipulation or analysis.