In a data mapping, you might need to identify missing or unwanted data when a source or target field contains compound data. For example, consider a long_address field that has this format:

number street apartment city state zip zip+4 country

Suppose that you want to separate the long_address field into discrete fields for number, street, city, state, and zip. To do this, you select long_address as the source field and then select the target fields. You then add padding fields at the locations for the parts of the source field that you do not want. In this example, the unwanted parts are apartment, zip+4, and country.

To identify the unwanted parts, you need to know the order of the parts. The order indicates an index for each part of the content in the compound field. For example, the long_address field has 8 ordered parts. Starting at 1, the index of each part is:

1

number

2

street

3

apartment

4

city

5

state

6

zip

7

zip+4

8

country

In the data mapper, to identify apartment, zip+4, and country as missing, you add padding fields at indexes 3, 7, and 8. See [separate-one-source-field-into-multiple-target-fields].

Now suppose that you want to combine source fields for number, street, city, state, and zip into a long_address target field. Further suppose that there are no source fields to provide content for apartment, zip+4, and country. In the data mapper, you need to identify these fields as missing. Again, you add padding fields at indexes 3, 7, and 8. See [combine-multiple-source-fields-into-one-target-field].