Applying Transformations
You can apply a transformation to a single attribute, or you can filter the attributes by a name pattern or data type and then use the Actions menu to apply a transformation to the group of filtered attributes.
The following attribute transformations are available.
This transformation lets you change the text case in an attribute, and add an attribute to hold the transformed data.
You can apply the transformation on a single attribute, or you can filter the attributes by a name pattern or data type and then do a bulk transformation on a group of attributes.
This transformation lets you change the data type of an attribute, and add an attribute to hold the transformed data.
You can apply the transformation on a single attribute, or you can filter the attributes by a name pattern or data type, and then do a bulk transformation on a group of attributes.
Create Unique ID transformation lets you add an attribute to the dataset. The values for the attribute are filled with a 128-bit universally unique identifier (UUID).
This transformation excludes the entire attribute and the data within from the data entity.
You can apply the transformation on a single attribute, or you can filter the attributes by a name pattern or data type and then do a bulk transformation on a group of attributes.
This transformation lets you search the dataset for specific data values to extract into a new attribute.
You can apply the transformation on a single attribute, or you can filter the attributes by a name pattern or data type and then do a bulk transformation on a group of attributes.
The format transformation lets you to apply a specific formatting rule such as a date or number format to the data.
You can apply the transformation on a single attribute, or you can filter the attributes by a name pattern or data type and then do a bulk transformation on a group of attributes.
For a single attribute: From the Transformations menu on the header of the attribute you want to transform, select Format.
For a group of attributes: Filter the attributes by using a name pattern or data type. Then click the Actions menu, and select Format.
- To filter by a name pattern, enter a simple regex pattern using wildcards (
?and*) in the Search by pattern field. - To filter by a Data Type, select a type from the menu. All data types is the default.
- To filter by a name pattern, enter a simple regex pattern using wildcards (
- In the Formatting dialog or panel, the options that are available depend on the attribute data type:
- For String, select the Trimming method (Trim Left, Trim Right, or Trim Both).
- For Number, enter a value in Decimal Places (optional).
- For Date, select the date format, and select or clear the Display Time checkbox as required.
- (Optional) Select Keep Source Attributes to keep the original attribute in the data.
- (Optional) Do one of the following, depending on whether you're transforming a single attribute or a group of attributes:
- For Name, enter a new name for the attribute or leave the name as-is.
- For New attribute name pattern, by default
$0is entered, which represents the entire matched string. You can leave the name as-is or you can replace the name with a suffix or prefix. For example, enter$0_REVISEDto append a suffix, or enterPREFIX_$0to add a prefix to the matched string.
- Select the Data Type of the transformed attribute.
- If applicable, enter the Length of the transformed attribute.
- Click Apply.
The hash transformation lets you to encrypt data, and generate encrypted values for attributes.
You can apply the transformation on a single attribute, or you can filter the attributes by a name pattern or data type and then do a bulk transformation on a group of attributes.
For a single attribute: From the Transformations menu on the header of the attribute you want to transform, select Hash.
For a group of attributes: Filter the attributes by using a name pattern or data type. Then click the Actions menu, and select Hash.
- To filter by a name pattern, enter a simple regex pattern using wildcards (
?and*) in the Search by pattern field. - To filter by a Data Type, select a type from the menu. All data types is the default.
- To filter by a name pattern, enter a simple regex pattern using wildcards (
- In the Hash dialog or panel:
- Select the hash type (MD5, SHA1, or SHA2).
- If applicable, select the number of bits.
- (Optional) Select Keep Source Attributes to keep the original attribute in the data.
- (Optional) Do one of the following, depending on whether you're transforming a single attribute or a group of attributes:
- For Name, enter a new name for the attribute or leave the name as-is.
- For New attribute name pattern, by default
$0is entered, which represents the entire matched string. You can leave the name as-is or you can replace the name with a suffix or prefix. For example, enter$0_REVISEDto append a suffix, or enterPREFIX_$0to add a prefix to the matched string.
- Select the Data Type of the transformed attribute.
- If applicable, enter the Length of the transformed attribute.
- Click Apply.
This transformation lets you merge two or more attributes into a new attribute.
This transformation lets you populate null data values in an attribute with a text string, and add an attribute to hold the transformed data values.
You can apply the transformation on a single attribute, or you can filter the attributes by a name pattern or data type and then do a bulk transformation on a group of attributes.
This transformation renames an attribute.
You can apply the transformation on a single attribute, or you can filter the attributes by a name pattern or data type and then do a bulk transformation on a group of attributes.
This transformation lets you replace data values in an attribute, and add an attribute to hold the transformed data.
You can apply the transformation on a single attribute, or you can filter the attributes by a name pattern or data type and then do a bulk transformation on a group of attributes.
This transformation lets you enter a regular expression to search and replace data values in an attribute, and add an attribute to hold the transformed data.
You can apply the transformation on a single attribute, or you can filter the attributes by a name pattern or data type and then do a bulk transformation on a group of attributes.
The sort transformation lets you sort data in ascending or descending order.
You can apply the transformation on a single attribute, or you can filter the attributes by a name pattern or data type and then do a bulk transformation on a group of attributes.