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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

Match Performance in Identity Analysis

Match Performance in Identity Analysis

To improve the mapping performance when you perform identity analysis on two data sets, configure the Match transformation to read identity index data from database tables. Run a mapping to create the index tables for the master data set. Run the mapping again to compare the index data to another data source.
Use the options on the
Match Type
view to identify the database tables that store the index data. Use the same options to select the index tables when you configure the transformation to compare the index data to data from another source.
To write the index data to database tables, perform the following tasks:
  1. Create a mapping that reads a data source of identity information.
  2. Configure a Match transformation in the mapping to write the index data to a database.
  3. Run the mapping to generate the index data. The index data represents a data store that you can reuse.
To read the index data from database tables, perform the following tasks:
  1. Create a mapping that reads another identity data source.
  2. Configure a Match transformation in the mapping to read the index data from the database that you specified earlier.
    When the mapping data source and the index data share a common structure, you can reuse the mapping that generated the index data.
  3. Run the mapping to compare the data source to the index data.
    The mapping generates index data for the data source. The mapping does not need to generate index data for the larger data set. Therefore, the mapping runs faster than a dual-source mapping that generates index data for both data sets.

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