You can edit an existing semantic type in Talend Dictionary Service to impact how your data is validated in Talend Data Preparation.
Predefined semantic types in Talend Data Preparation are based on standard values, but you may need to tailor them to match your own data. Some data that you would expect to fall under a predefined category, may be considered invalid.
Let's take the example of a dataset containing a list of customers, with their email addresses, date of birth, and the country they live in. You can notice that all the entries for United States of America are considered invalid, when they should not since it is the official name of the country.
The problem here is that United States of America is not one of
the expected value for the
country semantic type in Talend Data Preparation. The valid entry in this
case would be United States.
To avoid having this problem in the future, you will update the
semantic type in Talend Dictionary Service, and add
United States of America to the list of valid entries. The change
will be automatically available in Talend Data Preparation.
- Open the Semantic types view from the left panel of the Talend Data Preparation homepage.
From the list of existing semantic types, click the
Country type to open it.
In this window, all the parameters of the semantic type ca be modified, including the list of entries used to discover or validate data.
- In the Values list, point your mouse over the United States entry and click the pen icon that is displayed on the right.
- Right after United States, enter United States of America as second value, separated by a comma.
Click the tick icon to validate your change.
Those two values, that were entered in the same row, are now set as synonyms. As a consequence, United States of America will now be considered a valid value for the
Click Save and publish to propagate the change in
Talend Dictionary Service and
make it available to the Talend Data Preparation users.
The change in semantic types is instantly effective in Talend Data Preparation for every new dataset that you import. For existing datasets, you need to duplicate the column or reimport your dataset.
- Go back to your dataset with the column containing the customers countries.
Duplicate the column with the updated semantic type applied,
Country in this case.
You can see in the quality bar under the column header that there is no invalid values anymore.
country semantic type has been manually updated to support a new
From now on, when dealing with data that are matched with the
country semantic type, United States of
America will be considered a valid value.