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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

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Viewing Match Cluster Analysis Data

Viewing Match Cluster Analysis Data

You can view statistical data on the clusters that the transformation can create. The cluster statistics summarize the level of record duplication in the data set based on the current mapping configuration.
To view the data, right-click the Match transformation in the mapping canvas and select
Match Cluster Analysis
.
Before you run the analysis, validate the mapping that contains the transformation.
Match cluster 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 clusters
The number of clusters that the match analysis generates when the mapping runs.
Minimum cluster size
The number of records in the cluster or clusters that contain the fewest records. If the minimum cluster size is 1, the data set contains at least one unique record.
Maximum cluster size
The number of records in the cluster or clusters that contain the most records.
If this value greatly exceeds the average cluster size, the largest cluster might contain false duplicates.
Number of unique records
The number of records in the data set that do not match another record with a score that meets the match threshold.
Number of duplicate records
The number of records in the data set that match another record with a score that meets the match threshold.
Total comparisons
The number of comparison operations that the mapping performs.
Average cluster size
The average number of records in a cluster.
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