Mapping helps to extend the rule evaluation across datasets and fields. It helps to establish a corelation between the reference data assets to the corresponding assets.
Mapping for datasets
The next step in rule evaluation after the pass conditions are defined is to map the
fields in the dataset. Once the field is selected in the initial section in the pass
condition from the reference dataset, you can proceed to map the fields. A few
fields are auto mapped, and a few other fields must be mapped manually. When
additional attributes are added to the pass condition, these must be mapped
individually. When the additional attributes are mapped, the mapping status is
updated automatically.
Note: The rule cannot be saved if all
the fields added in pass conditions are not mapped.
To map fields with the reference dataset :
- After the pass conditions are defined, click Map Fields.
- The page displays details of the number of fields that are auto mapped and the number fields that require mapping.
- It also displays an error message if the datatype in the added fields don’t match the reference dataset.
- Clicking on the respective section will navigate you to the respective fields where mapping is required or the auto-mapped fields that require verification.
- For example, if the needs mapping section displays the value as (0/7), it indicates that 0 out of 7 fields have been mapped and 7 fields require mapping. On clicking the arrow, you will be navigated to the consecutive fields wherein you can verify and map the fields.
- You can view the mapping status and the details of the reference and target datasets.
- For the unmapped fields, select the fields that must be mapped with the field in the reference dataset and proceed to map the fields manually.
- For the automapped fields, verify the field that is auto-mapped.
- Click Review and Save .
Note: The mapping operation can be performed only if the
selected datasets are of the same datatype. Only those fields that have the same
datatype and field name are auto mapped and those datasets that have the same
datatype but different field names have to be mapped manually.
Mapping for fields
Mapping functionality can be extended to the fields in the dataset. After the required fields are selected in the target assets section, proceed to map the fields.
To map the fields:
- After the pass conditions are defined, click Map Fields.
- The page displays details of the number of fields that are auto mapped and the number of fields that require mapping and displays an error message if the datatype in the added fields don’t match the reference dataset.
- Clicking on the respective sections will navigate you to those fields that need mapping or to the auto-mapped fields that require verification.
- For example, if the needs mapping section displays the value as(1/4), it indicates that 1 out of 4 fields have been mapped and 3 more fields require mapping. On clicking the arrow, you will be navigated to the consecutive fields wherein you can verify and map the fields.
- For the unmapped fields, map the fields manually with the reference dataset .
- For the automapped fields, verify the field that is auto-mapped.
- You can view the mapping status and the details of the reference and target fields.
- The field that is part of the reference dataset is treated as the reference field and all the other fields must be mapped accordingly.
- Click Review and Save.
Change reference dataset
The reference dataset can be changed for the target assets if you would want to compare and map the existing fields with another dataset.
To change the reference dataset :
- Click Change Reference Dataset in the pass conditions.
- This would display the list of datasets added in the rule.
- Select the dataset that you would want to have as the reference for pass conditions.
- Click Save.
Note: If the reference dataset is changed, the fields must be
mapped again in the pass condition based on the updated reference dataset.