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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

Row-Based Strategies

Row-Based Strategies

A row-based strategy analyzes rows in the record group and selects one row. The Consolidation transformation uses the port values from that row to create a consolidated record. The default strategy is "most data."
Choose one of the following row-based strategies:
Most data
Selects the row with the highest character count. If the highest character count is shared by two or more rows, the strategy returns the last qualifying value.
Most filled
Selects the row with the highest number of non-blank columns. If the highest number of non-blank columns is shared by two or more rows, the strategy returns the last qualifying value.
Modal exact
Selects the row with the highest count of the most frequent non-blank values. For example, consider a row that has three ports that contain the most frequent values in the record group. The count of the most frequent values for that row is "3."
If the highest count of the most frequent non-blank values is shared by two or more rows, the strategy returns the last qualifying value.

Row-Based Strategy Example

The following table displays a sample record group. The last column describes the reasons why specific row-based strategies select different rows in this record group.
Product ID
First Name
Last Name
ZIP Code
Strategy Selection
2106
Bartholomew
28516
The Most Data strategy selects this row because the row contains more characters than the other rows.
2236
Bart
Smith
28579
The Most Filled strategy selects this row because the row has more non-blank columns than the other rows.
2236
<Blank>
Smith
28516
The Modal Exact strategy selects this row because the row contains the highest count of the most frequent values.

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