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

Run the Data Viewer

Run the Data Viewer

Run the Data Viewer to review the results of the match analysis. By default, the Data Viewer shows all the output ports on the Match transformation. When you run the mapping, you update the data target with the data from the output ports.
The following image shows the output data in the Data Viewer:
The Data Viewer shows the output data from the Match transformation output ports, including the row I.D. ports.
The Data Viewer verifies that the customer account data includes one or more duplicate records.
Consider the following data in the Data Viewer:
  • The transformation determines that the records for Augusta Chan and Carmen Chan might contain the same information because they contain the same surname and address data. When you review the records, you decide that the records are unique in the data set. However, you notice that the records share a common customer ID value. Because the customer ID column is a primary key in the data set, you contact the New York office. The New York office resolves the error.
  • The transformation determines that the records for Keith Anderson might contain the same information. When you review the records, you verify that the two records represent the same account. However, you notice that the records have different customer ID values. Because a customer account must have a single ID value, you contact the San Antonio office. The San Antonio office resolves the error.

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