Table of Contents

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  1. Preface
  2. Introduction to Informatica Data Engineering Integration
  3. Mappings
  4. Mapping Optimization
  5. Sources
  6. Targets
  7. Transformations
  8. Python Transformation
  9. Data Preview
  10. Cluster Workflows
  11. Profiles
  12. Monitoring
  13. Hierarchical Data Processing
  14. Hierarchical Data Processing Configuration
  15. Hierarchical Data Processing with Schema Changes
  16. Intelligent Structure Models
  17. Blockchain
  18. Stateful Computing
  19. Appendix A: Connections Reference
  20. Appendix B: Data Type Reference
  21. Appendix C: Function Reference

Profiles Overview

Profiles Overview

You can create and run column profiles, enterprise discovery profiles, and scorecards in the native run-time environment or Hadoop run-time environment.
When you create or edit a profile or scorecard, you can choose Native or Hadoop validation environment. You can choose the Native, Blaze, or Spark run-time environment based on the validation environment. To process the profiles quickly, you can choose the Hadoop validation environment. You can run profiles with a Hive, Oracle, or HDFS data sources on the Spark engine in the Hadoop environment.


Updated September 28, 2020