Table of Contents

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  1. Preface
  2. Introduction to Transformations
  3. Transformation Ports
  4. Transformation Caches
  5. Address Validator Transformation
  6. Aggregator Transformation
  7. Association Transformation
  8. Bad Record Exception Transformation
  9. Case Converter Transformation
  10. Classifier Transformation
  11. Comparison Transformation
  12. Consolidation Transformation
  13. Data Masking Transformation
  14. Data Processor Transformation
  15. Decision Transformation
  16. Duplicate Record Exception Transformation
  17. Expression Transformation
  18. Filter Transformation
  19. Hierarchical to Relational Transformation
  20. Java Transformation
  21. Java Transformation API Reference
  22. Java Expressions
  23. Joiner Transformation
  24. Key Generator Transformation
  25. Labeler Transformation
  26. Lookup Transformation
  27. Lookup Caches
  28. Dynamic Lookup Cache
  29. Match Transformation
  30. Match Transformations in Field Analysis
  31. Match Transformations in Identity Analysis
  32. Normalizer Transformation
  33. Merge Transformation
  34. Parser Transformation
  35. Python Transformation
  36. Rank Transformation
  37. Read Transformation
  38. Relational to Hierarchical Transformation
  39. REST Web Service Consumer Transformation
  40. Router Transformation
  41. Sequence Generator Transformation
  42. Sorter Transformation
  43. SQL Transformation
  44. Standardizer Transformation
  45. Union Transformation
  46. Update Strategy Transformation
  47. Web Service Consumer Transformation
  48. Parsing Web Service SOAP Messages
  49. Generating Web Service SOAP Messages
  50. Weighted Average Transformation
  51. Window Transformation
  52. Write Transformation
  53. Appendix A: Transformation Delimiters

Developer Transformation Guide

Developer Transformation Guide

Substitution Masking Properties

Substitution Masking Properties

You can configure the following masking rules for substitution masking:
  • Repeatable Output
    . Returns deterministic results between sessions. The Data Masking transformation stores masked values in the storage table.
  • Seed Value.
    Apply a seed value to generate deterministic masked data for a column. Enter a number between 1 and 1,000.
  • Unique Output
    . Force the Data Masking transformation to create unique output values for unique input values. No two input values are masked to the same output value. The dictionary must have enough unique rows to enable unique output.
    When you disable unique output, the Data Masking transformation might not mask input values to unique output values. The dictionary might contain fewer rows.
  • Unique Port
    . The port used to identify unique records for substitution masking. For example, you want to mask first names in a table called Customer. If you select the table column that contains the first names as the unique port, the data masking transformation replaces duplicate first names with the same masked value. If you select the Customer_ID column as the unique port, the data masking transformation replaces each first name with a unique value.
  • Dictionary Information
    . Configure the reference table that contains the substitute data values. Click
    Select Source
    to select a reference table.
    • Dictionary Name
      . Displays the name of the reference table that you select.
    • Output Column
      . Choose the column to return to the Data Masking transformation.
  • Lookup condition.
    Configure a lookup condition to further qualify what dictionary row to use for substitution masking. The lookup condition is similar to the WHERE clause in an SQL query. When you configure a lookup condition you compare the value of a column in the source with a column in the dictionary.
    For example, you want to mask the first name. The source data and the dictionary have a first name column and a gender column. You can add a condition that each female first name is replaced with a female name from the dictionary. The lookup condition compares gender in the source to gender in the dictionary.
    • Input port
      . Source data column to use in the lookup.
    • Dictionary column
      . Dictionary column to compare the input port to.

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