Hi, I'm Ask INFA!
What would you like to know?
ASK INFAPreview
Please to access Ask INFA.

Table of Contents

Search

  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

Labeler Transformation Overview

Labeler Transformation Overview

The Labeler transformation is a passive transformation that analyzes input port fields and writes text labels that describe the data in each field.
You use a Labeler transformation when you want to understand the types of information that a port contains. Use a Labeler transformation when you do not know the types of information on a port, or when you want to identify records that do not contain the expected types of information on a port.
A label is a string one or more characters that describes an input string. You configure the Labeler transformation to assign labels to input strings based on the data that each string contain.
When you configure the transformation, you specify the types of character or string to search for, and you specify the label that the transformation writes as output when it finds the associated character or string. You enter the character and string types to search for, and the labels to use, when you configure a labeling operation. Or, you use reference data objects to specify the characters, strings, and labels.
You configure the transformation to perform character labeling or token labeling:
Character Labeling
Writes a label that describes the character structure of the input string, including punctuation and spaces. The transformation writes a single label for each row in a column. For example, the Labeler transformation can label the ZIP Code 10028 as "nnnnn," where "n" stands for a numeric character.
Token Labeling
Writes a label that describes the type of information in the input string. The transformation writes a label for each token identified in the input data. For example, you can configure the Labeler transformation to label the string "John J. Smith" with the tokens "Word Init Word."
A token is a delimited value in an input string.
When the Labeler finds a character or string that matches a label that you specify, it writes the label name to a new output port.
The Labeler transformation uses reference data to identify characters and tokens. You select the reference data object when you configure an operation in a Labeler strategy.

0 COMMENTS

We’d like to hear from you!