Table of Contents

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

Informatica Big Data Management Overview

Informatica Big Data Management Overview

Informatica Big Data Management enables your organization to process large, diverse, and fast changing data sets so you can get insights into your data. Use Big Data Management to perform big data integration and transformation without writing or maintaining external code.
Use Big Data Management to collect diverse data faster, build business logic in a visual environment, and eliminate hand-coding to get insights on your data. Consider implementing a big data project in the following situations:
  • The volume of the data that you want to process is greater than 10 terabytes.
  • You need to analyze or capture data changes in microseconds.
  • The data sources are varied and range from unstructured text to social media data.
You can perform run-time processing in the native environment or in a non-native environment. The native environment is the Informatica domain where the Data Integration Service performs all run-time processing. Use the native run-time environment to process data that is less than 10 terabytes. A non-native environment is a distributed cluster outside of the Informatica domain, such as Hadoop or Databricks, where the Data Integration Service can push run-time processing. Use a non-native run-time environment to optimize mapping performance and process data that is greater than 10 terabytes.


Updated July 10, 2020