Table of Contents

Search

  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

Social Media Mappings

Social Media Mappings

Create mappings to read social media data from sources such as Facebook and LinkedIn.
You can extract social media data and load them to a target in the native environment only. You can choose to parse this data or use the data for data mining and analysis.
To process or analyze the data in Hadoop, you must first move the data to a relational or flat file target and then run the mapping in the Hadoop cluster.
You can use the following Informatica adapters in the Developer tool:
  • PowerExchange for DataSift
  • PowerExchange for Facebook
  • PowerExchange for LinkedIn
  • PowerExchange for Twitter
  • PowerExchange for Web Content-Kapow Katalyst
Review the respective PowerExchange adapter documentation for more information.


Updated September 28, 2020