Table of Contents

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  1. Preface
  2. Introduction to Informatica Big Data Management
  3. Mappings in the Hadoop Environment
  4. Mapping Sources in the Hadoop Environment
  5. Mapping Targets in the Hadoop Environment
  6. Mapping Transformations in the Hadoop Environment
  7. Processing Hierarchical Data on the Spark Engine
  8. Configuring Transformations to Process Hierarchical Data
  9. Processing Unstructured and Semi-structured Data with an Intelligent Structure Model
  10. Stateful Computing on the Spark Engine
  11. Monitoring Mappings in the Hadoop Environment
  12. Mappings in the Native Environment
  13. Profiles
  14. Native Environment Optimization
  15. Cluster Workflows
  16. Connections
  17. Data Type Reference
  18. Function Reference
  19. Parameter Reference

Big Data Management Tasks

Big Data Management Tasks

Use Big Data Management when you want to access, analyze, prepare, transform, and stream data faster than traditional data processing environments.
You can use Big Data Management for the following tasks:
  • Read from and write to diverse big data sources and targets.
  • Perform data replication on a Hadoop cluster.
  • Perform data discovery.
  • Perform data lineage on big data sources.
  • Stream machine data.
  • Manage big data relationships.
  • Create ephemeral clusters.
The
Informatica Big Data Management User Guide
describes how to run big data mappings in the native environment or the Hadoop environment. For information on specific license and configuration requirements for a task, refer to the related product guides.


Updated October 23, 2019