Table of Contents

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  1. Preface
  2. Transformations
  3. Source transformation
  4. Target transformation
  5. Access Policy transformation
  6. Aggregator transformation
  7. B2B transformation
  8. Chunking transformation
  9. Cleanse transformation
  10. Data Masking transformation
  11. Data Services transformation
  12. Deduplicate transformation
  13. Expression transformation
  14. Filter transformation
  15. Hierarchy Builder transformation
  16. Hierarchy Parser transformation
  17. Hierarchy Processor transformation
  18. Input transformation
  19. Java transformation
  20. Java transformation API reference
  21. Joiner transformation
  22. Labeler transformation
  23. Lookup transformation
  24. Machine Learning transformation
  25. Mapplet transformation
  26. Normalizer transformation
  27. Output transformation
  28. Parse transformation
  29. Python transformation
  30. Rank transformation
  31. Router transformation
  32. Rule Specification transformation
  33. Sequence transformation
  34. Sorter transformation
  35. SQL transformation
  36. Structure Parser transformation
  37. Transaction Control transformation
  38. Union transformation
  39. Vector Embedding transformation
  40. Velocity transformation
  41. Verifier transformation
  42. Web Services transformation

Transformations

Transformations

Run the mapping

Run the mapping

You can choose to run the mapping directly or to add the mapping to a mapping task.

Run the mapping directly

  1. On the mapping page, click
    Run
    .
  2. Enter values that you want to use for the source, target, and masking techniques in this run.
  3. Click
    Run
    .
You can monitor the progress and status of the mapping job on the
My Jobs
tab. You can access and run the mapping again to run it with different values. Wait for the first job to complete before you run the mapping again.

Run a mapping task

  1. From the
    Actions
    menu on the mapping page, click
    New Mapping Task
    .
  2. On 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. On the
    Sources
    tab, perform the following steps:
    1. Select the source connection on which you want to run the mapping task.
    2. If 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. On the
    Targets
    tab, perform the following steps:
    1. Select the target connection to which you want to load the masked data.
    2. If you used an object type parameter in the target transformation, select the object.
    3. Select the operation type and other target configuration options, and then click
      Next
      .
      The object that you specify must already exist. You cannot create the target object at runtime.
  5. Optional. 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. Click
    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. Optional. 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. Click
    Save
    to save the mapping task.
  9. Click
    Run
    to run the mapping task. You can monitor the progress and status of the mapping task on the
    My Jobs
    tab.
You can run the masking task again with updated parameter values to mask different or new source data. Wait for the masking task to complete before you run it again.

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