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Table of Contents

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  1. Preface
  2. Working with Transformations
  3. Address Validator Transformation
  4. Aggregator Transformation
  5. Association Transformation
  6. Bad Record Exception Transformation
  7. Case Converter Transformation
  8. Classifier Transformation
  9. Cleanse transformation
  10. Comparison Transformation
  11. Custom Transformation
  12. Custom Transformation Functions
  13. Consolidation Transformation
  14. Data Masking Transformation
  15. Data Masking Examples
  16. Decision Transformation
  17. Duplicate Record Exception Transformation
  18. Dynamic Lookup Cache
  19. Expression Transformation
  20. External Procedure Transformation
  21. Filter Transformation
  22. HTTP Transformation
  23. Identity Resolution Transformation
  24. Java Transformation
  25. Java Transformation API Reference
  26. Java Expressions
  27. Java Transformation Example
  28. Joiner Transformation
  29. Key Generator Transformation
  30. Labeler Transformation
  31. Lookup Transformation
  32. Lookup Caches
  33. Match Transformation
  34. Match Transformations in Field Analysis
  35. Match Transformations in Identity Analysis
  36. Merge Transformation
  37. Normalizer Transformation
  38. Parser Transformation
  39. Rank Transformation
  40. Router Transformation
  41. Sequence Generator Transformation
  42. Sorter Transformation
  43. Source Qualifier Transformation
  44. SQL Transformation
  45. Using the SQL Transformation in a Mapping
  46. Stored Procedure Transformation
  47. Standardizer Transformation
  48. Transaction Control Transformation
  49. Union Transformation
  50. Unstructured Data Transformation
  51. Update Strategy Transformation
  52. Weighted Average Transformation
  53. XML Transformations

Transformation Guide

Transformation Guide

Dictionaries

Dictionaries

A dictionary is a flat file or relational table that contains the substitute data for each row in the file. The Data Masking transformation generates a number to retrieve a dictionary row. The Data Masking transformation generates a hash key for repeatable substitution masking or a random number for non-repeatable masking. You can configure an additional lookup condition.
You can configure a dictionary to mask more than one port in the Data Masking transformation.
The following example shows a flat file dictionary that contains first name and gender:
SNO,GENDER,FIRSTNAME 1,M,Adam 2,M,Adeel 3,M,Adil 4,F,Alice 5,F,Alison
In this dictionary, the first field in the row is the serial number, and the second field is gender. You can add gender as a lookup condition. The Integration Service retrieves a row from the dictionary using a hash key, and it finds a row with a gender that matches the gender in the source data.
Use the following rules and guidelines when you create a dictionary:
  • The first row of a flat file dictionary must have column labels to identify the fields in each record. The fields are separated by commas. If the first row does not contain column labels, the Integration Service takes the values of the fields in the first row as column names.
  • A flat file dictionary must be in the $PMLookupFileDir lookup file directory.
  • If you create a flat file dictionary on Windows and copy it to a UNIX machine, verify that the file format is correct for UNIX. For example, Windows and UNIX use different characters for the end of line marker.
  • If you configure substitution masking for more than one port, all relational dictionaries must be in the same database schema.
  • The line sequential buffer length of a flat file dictionary must be less than or equal to 600 characters.
  • You cannot change the dictionary type or the substitution dictionary name in session properties.

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