Communities
A collaborative platform to connect and grow with like-minded Informaticans across the globe
Product Communities
Connect and collaborate with Informatica experts and champions
Discussions
Have a question? Start a Discussion and get immediate answers you are looking for
User Groups
Customer-organized groups that meet online and in-person. Join today to network, share ideas, and get tips on how to get the most out of Informatica
Get Started
Community Guidelines
Knowledge Center
Troubleshooting documents, product guides, how to videos, best practices, and more
Knowledge Base
One-stop self-service portal for solutions, FAQs, Whitepapers, How Tos, Videos, and more
Support TV
Video channel for step-by-step instructions to use our products, best practices, troubleshooting tips, and much more
Documentation
Information library of the latest product documents
Velocity (Best Practices)
Best practices and use cases from the Implementation team
Learn
Rich resources to help you leverage full capabilities of our products
Trainings
Role-based training programs for the best ROI
Certifications
Get certified on Informatica products. Free, Foundation, or Professional
Product Learning Paths
Free and unlimited modules based on your expertise level and journey
Resources
Library of content to help you leverage the best of Informatica products
Tech Tuesdays Webinars
Most popular webinars on product architecture, best practices, and more
Product Availability Matrix
Product Availability Matrix statements of Informatica products
SupportFlash
Monthly support newsletter
Support Documents
Informatica Support Guide and Statements, Quick Start Guides, and Cloud Product Description Schedule
Product Lifecycle
End of Life statements of Informatica products
Ideas
Events
Change Request Tracking
Marketplace
English
  • Informatica Data Quality 10.4.1
  • All Products

Table of Contents

Search

  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. Macro Transformation
  30. Match Transformation
  31. Match Transformations in Field Analysis
  32. Match Transformations in Identity Analysis
  33. Normalizer Transformation
  34. Merge Transformation
  35. Parser Transformation
  36. Python Transformation
  37. Rank Transformation
  38. Read Transformation
  39. Relational to Hierarchical Transformation
  40. REST Web Service Consumer Transformation
  41. Router Transformation
  42. Sequence Generator Transformation
  43. Sorter Transformation
  44. SQL Transformation
  45. Standardizer Transformation
  46. Union Transformation
  47. Update Strategy Transformation
  48. Web Service Consumer Transformation
  49. Parsing Web Service SOAP Messages
  50. Generating Web Service SOAP Messages
  51. Weighted Average Transformation
  52. Window Transformation
  53. Write Transformation
  54. Appendix A: Transformation Delimiters

Developer Transformation Guide

Developer Transformation Guide

Back Next

Creating a Read Transformation in the Mapping Editor

Creating a Read Transformation in the Mapping Editor

You can create a Read transformation to represent the source of data and column metadata and properties in a mapping.
Perform the following steps:
  1. Choose one of the following methods to create a Read transformation:
    • Right-click in the mapping editor and select
      Add Transformation
      .
      The
      Add Transformation
       dialog box opens.
      Select Read transformation and click
      Next
      .
    • Scroll down in the mapping palette to locate and double-click the Read transformation icon.
      The following image shows the Read transformation icon:
    The
    New Read Transformation
     dialog box opens.
  2. To use a flat file, a relational resource, or a customized data object as the source, perform the following steps:
    1. Select
      Physical Data Object
       as the data object type.
    2. Click
      Browse
       to select a flat file, a relational resource, or a customized data object.
      The
      Select Data Object
       window opens.
    3. Select a data object and click
      OK
      .
    4. Optionally, configure the transformation to fetch data object columns from the source at run time. Select
      At run-time, get data object columns from data source
      .
      The Data Integration Service refreshes column metadata for the Read transformation when the mapping runs.
  3. To use a parameter as the source, perform the following steps:
    1. Select
      Create using a parameter
      .
    2. Click
      New
       to create a new parameter, or click
      Browse
       to select an existing parameter.
    3. Select a parameter and click
      OK
      .
    4. Optionally, configure the transformation to fetch data object columns from the source at run time. Select
      At run-time, get data object columns from data source
      .
      The Data Integration Service refreshes column metadata for the Read transformation when the mapping runs.
  4. To use a logical data object as the source, perform the following steps:
    1. Select
      Logical Data Object
       as the data object type.
    2. Click
      Browse
       to select a data object, and then click
      OK
      .
  5. Optionally, type a name for the Read transformation.
  6. Click
    Finish
    .
0 COMMENTS
We’d like to hear from you!