Mask rule parameter example

• •You create a mapping with a specific source and target and add the masking techniques as well. Over time, you add on more columns to the source table and want to mask those columns as well. The mapping then needs to be edited before it can be run again. To avoid having to edit the mapping, you can use a mask rule parameter when you configure it. You can then select columns to mask at runtime. If you added any columns after the mapping was created, you can select them at runtime without updating the mapping.
• •You might have source data in multiple databases. Rather than creating multiple mappings for each source and target combination, you might want to create a single mapping to mask your source data in any of the databases and load them to different target databases. To run a mapping with different source and target connections each time, you can use parameters for the source and target connections and objects. You then need to choose different masking techniques depending on the source connection. To do this, add a mask rule parameter to the data masking transformation in your mapping. You can then choose the source connection and object, the masking rules to apply to each column, and the target connection and object at runtime. You can run the same mapping multiple times after selecting different values for these fields depending on which source and target you want to use.

1. 1Create a mapping with parameters.
2. 2Run the mapping. You can run a mapping directly or from a mapping task.

Create a mapping with parameters

1. 1Log in toInformatica Intelligent Cloud Services and open Data Integration.
2. 2Click New > Mappings > Mapping to open a new mapping in the mapping designer.
3. 3Configure the source transformation.
Optionally, use a parameter for the connection. If you use a parameter, and the object names in each source differ or you don't know the object name, ensure that you use a parameter for the object. If the object name is the same in all sources that you plan to use this mapping with, you can choose the source type as single object and then enter the object name.
4. 4Configure the target transformation.
Optionally, use a parameter for the connection. If the object names in each target differ or you don't know the object name, ensure that you use a parameter for the object. If the object name is the same in all targets that you plan to use this mapping with, you can choose the target type as single object and then enter the object name. The object must exist when the mapping runs. You can't create the target object at runtime.
5. 5Drag a Data Masking transformation from the transformations palette onto the mapping designer and connect it to the data flow.
6. 6Select the Data Masking transformation object in the mapping designer. The properties appear on the Properties tab.
7. 7On the General tab, enter a name and optional description for the transformation object.
8. 8On the Masking Rules tab, select Add a parameter to configure masking techniques at runtime.
9. 9Click New Parameter and create a masking parameter. Then select the parameter from the list.
The following image shows a sample masking_rules parameter created and selected:

10. 10Select a relational dictionary connection or a flat file dictionary connection and storage connection from the lists.
If you don't select values here, you can't add or update the values when you run the mapping.
11. 11Click Save to save the mapping.

Run the mapping

Run the mapping directly

1. 1On the mapping page, click Run.
2. 2Enter values that you want to use for the source, target, and masking techniques in this run.
3. 3Click Run.

Run a mapping task

1. 1From the Actions menu on the mapping page, click New Mapping Task.
2. 2On the Mapping Task page that opens, add a name and description, choose a runtime environment, select the mapping that you created, and click Next.
3. 3On the Sources tab, perform the following steps:
1. aSelect the source connection on which you want to run the mapping task.
2. bIf you used an object type parameter in the source transformation, select the source type Single and select an object. You can then preview the source data on the Data Preview tab.
4. 4On the Targets tab, perform the following steps:
1. aSelect the target connection to which you want to load the masked data.
2. bIf you used an object type parameter in the target transformation, select the object.
3. cSelect the operation type and other target configuration options, and then click Next.
Note: The object that you specify must already exist. You cannot create the target object at runtime.
5. 5Optional. On the Input Parameters tab, if you need to change the dictionaries or storage connection that you previously included, select the connections from the list. You can ignore the fields if you don't need to use the connections.
6. 6Click Add to add a field and then click Configure to select the masking technique that you want to apply to the field. Repeat this for each field that you want to mask and then click Next.
7. 7Optional. On the Runtime Options tab, choose scheduling and notification options as needed.
If you want to update the parameter values in each run, skip the scheduling options. You can't change parameter values before an automated run.
8. 8Click Save to save the mapping task.
9. 9Click Run to run the mapping task. You can monitor the progress and status of the mapping task on the My Jobs tab.