Registered users of this product or Trifacta Wrangler Enterprise should login to Product Docs through the application.
Use the following functions to identify if your data matches a specified data type or is missing or null.
Tip: It's typically easier to review and manipulate data types and their valid, mismatched, or missing values through the application. At the top of each column in the data grid, you can review the data quality bar, which contains color-coded identifiers of valid, invalid, or missing data for the currently selected data type. You can click each of these bars to perform transformations on each category of data, or you can select a new data type from the data type drop-down for the column to review data quality for the column under a different data type. See Data Grid Panel.
Null values require special handling. For more information, see Manage Null Values.
For more information on data types, see Supported Data Types.
When making references to a data type within your Wrangle transforms, you must reference the appropriate data type key. See Valid Data Type Strings.
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