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  • Informatica Data Quality 10.4.0
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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

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Viewing Match Performance Analysis Data

Viewing Match Performance Analysis Data

You can view statistical data on the record groups that the mapping reads as input data.
To view the data, right-click the Match transformation in the mapping canvas and select
Match Performance Analysis
.
Before you run the analysis, validate the mapping that contains the transformation.
Match performance analysis displays data for the following properties:
Property
Description
Source
The number of input data rows.
Last run
The date and time of the analysis.
Total number of discovered groups
The number of groups defined for the data set, based on the selected group key value.
Throughput (records per minute)
Variable value that estimates the speed of the match analysis. You set this value. Use the value to estimate the time required to run the match analysis.
Estimated time to match records
The time taken to analyze all records in the data set, based on the Match transformation configuration.
Total number of pairs generated
The number of comparisons that the transformation must perform, based on the number of input data rows and the number of groups.
Minimum group size
Variable value that indicates the minimum number of records a group can contain. You set this value. Use the value to verify that the mapping will create groups of a usable size.
The minimum group size value does not determine the size of the groups created when the mapping runs.
Number of groups below minimum threshold
The number of groups that contain fewer records than the minimum group size value.
If many groups are below the minimum group size, you might need to edit the transformation and select a different group key.
Maximum group size
Variable value that indicates the maximum number of records a group can contain. You set this value for the performance analysis. Use the value to verify that the mapping will create groups of a usable size.
The value does not determine the size of the groups created when the mapping runs.
Number of groups above maximum threshold
The number of groups that contain more records than the maximum group size value.
If many groups are above the maximum group size, you might need to edit the transformation and select a different group key.
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