Table of Contents

Search

  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

Merge Fields

Merge Fields

You can merge fields of similar data into a single multiple-occurring field in the
Normalizer
view. You might need to merge fields when you drag ports from another object to create a Normalizer transformation in a mapping.
A source row might contain multiple fields that contain different types of salary data, such as Base_Salary, Bonus_Pay, and Sales_Commissions. You can merge the fields to create one Salary field that occurs three times.
The following image shows an employee row with three types of salary selected in the Normalizer view:
The Normalizer tab shows the STORE field and four instances of the QUARTER field. Each field has an occurs value of one.
You can merge the three types of salary data into a Salary field that occurs three times.
The following image shows the Salary field:
The Normalizer view contains an EmployeeID field that occurs once. It also contains a Salary field that occurs 3 times.

0 COMMENTS

We’d like to hear from you!