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. Cleanse transformation
  9. Data Masking transformation
  10. Data Services transformation
  11. Deduplicate transformation
  12. Expression transformation
  13. Filter transformation
  14. Hierarchy Builder transformation
  15. Hierarchy Parser transformation
  16. Hierarchy Processor transformation
  17. Input transformation
  18. Java transformation
  19. Java transformation API reference
  20. Joiner transformation
  21. Labeler transformation
  22. Lookup transformation
  23. Machine Learning transformation
  24. Mapplet transformation
  25. Normalizer transformation
  26. Output transformation
  27. Parse transformation
  28. Python transformation
  29. Rank transformation
  30. Router transformation
  31. Rule Specification transformation
  32. Sequence transformation
  33. Sorter transformation
  34. SQL transformation
  35. Structure Parser transformation
  36. Transaction Control transformation
  37. Union transformation
  38. Velocity transformation
  39. Verifier transformation
  40. Web Services transformation

Transformations

Transformations

Access Policy transformation

Access Policy transformation

The Access Policy transformation applies
data protection policies
and
data filter policies
created in
Data Access Management
according to the properties of the Access Policy transformation. An access policy is a set of policies and associated
data protection rules
and
data filter rules
that apply
data protections
and filters that transform and filter the data accordingly.
Data protections
can replace, transform, or redact values in a data set while maintaining the overall usefulness of the data. An access policy can protect different values in different mappings, based on factors such as the intended user of the data and metadata classifications that users assign to the source data. Access policies can help your organization comply with data privacy regulations such as the European General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA).
Data protection rules
apply pre-defined
data protections
to data classes. A data class is a categorization applied to fields within data assets to indicate the category of data such as birth dates, national identifiers, and postal codes.
Rules in an access policy can apply multiple
data protection techniques
, including the following operations:
  • Retaining data
  • Redacting all values of a given type such as birth dates
  • Replacing specified field values with NULL
  • Truncating values such as redacting the first three characters of a postal code
  • Replacing values with consistently tokenized values such as always replacing "Smith" with "Abcd" or "1234" with "5678"
  • Generalizing date values to the month, year, or decade
  • Replacing values with a constant text value such as replacing all passwords with five asterisks
Data filters limit, filter, or otherwise restrict user access to data assets.
Data filter rules
apply pre-defined filters that control access to rows or records of data.
Rules in an access policy can apply multiple data filters based on the following attribute types:
  • User group
  • Order usage context
  • Asset term
An Access Policy transformation doesn't display the policies, since those are dynamically applied based on the data and metadata. Users with the appropriate permissions manage policies in
Data Access Management
.
Not all organizations have
Data Access Management
. Your organization has
Data Access Management
if it appears on the
My Services
page. If it doesn't appear, contact Informatica Global Customer Support to request
Data Access Management
.

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