In this example, you create a data model to determine the structure of the data to be managed in the Site deduplication campaign. This campaign enables data stewards to label near duplicates in a data sample extracted by a Talend Job.
Talend Cloud Data Stewardship has data model awareness which makes possible the syntactic and semantic validation of data. You can define the attributes in the data model and select their types out of a predefined standard or semantic types.
- Select .
Enter a name and a description for the
new model in the Name and Description fields respectively. Optional fields
are marked as optional next to their
In the Attributes
section, define the columns you want to have in the data model as the
- In the IDENTIFIER field, enter the technical identifier for the first column.
Enter a name and a description for the column in the
corresponding fields, if needed.
What you set in the NAME field is the name displayed in the task list. If no name is set, the technical identifier will be displayed.
From the attribute type list, select the type of the
Standard and semantic types are integrated in the application by default.
- For the standard types, additional fields are
displayed according to the type you select. These fields are
optional and they enable you to define some constraints on the
attribute you define such as defining a minimum and/or maximum
length or defining a pattern against which to validate the
To make sure the entire value matches your validation pattern, it is best practice to surround the validation pattern with
Abut does not match
Timestampcolumns, you have access to a date and time picker which helps you set the date and time automatically in the right format.
- For the semantic types, you can use the Talend Dictionary Service to manage the semantic types. However, the availability of this service depends on the license you have.
- For the standard types, additional fields are displayed according to the type you select. These fields are optional and they enable you to define some constraints on the attribute you define such as defining a minimum and/or maximum length or defining a pattern against which to validate the attribute.
- Optionally, toggle the ALLOW EMPTY VALUES option to disable the upload of empty fields. This option is enabled by default.
ATTRIBUTE and repeat the above steps to create all the columns
you need in the data model.
The columns defined for the Site deduplication campaign used in this example hold information about childhood education centers in Chicago.