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

Example

Example

Consider the following example:
The source data contains
First Name
and
Last Name
columns that you need to mask to ensure that you mask the full name in the target data.
You can use the following methods to generate the masked output:
  • Run a
    masking
    task on
    Informatica Intelligent Cloud Services
    .
  • Run a
    mapping
    task that contains a data masking transformation on
    Informatica Intelligent Cloud Services
    .
  • Run a mapping that contains a data masking transformation on
    Informatica Intelligent Cloud Services
  • Run a data masking plan in Test Data Management.
  • Run a PowerCenter mapping that contains a data masking transformation.
Perform the following high-level tasks to generate the masked output:
  1. Use the Substitution Name masking rule to mask the
    First Name
    column. Set the Repeatable option to ON. Enter a seed value.
  2. Use the Substitution Last Name masking rule to mask the
    Last Name
    column. Set the Repeatable option to ON. Enter a seed value.
  3. Use the default dictionaries available with the setup. Do not make changes to the dictionaries.
When you run the
masking
task, mapping, or
mapping
task on
Informatica Intelligent Cloud Services
, Test Data Management workflow, or PowerCenter mapping to generate output, you generate the same masked output for the same source data.

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