Preface
Introduction to Informatica Big Data Management
Mappings
Sources
Targets
Transformations
Data Preview
Cluster Workflows
Profiles
Monitoring
Hierarchical Data Processing
Hierarchical Data Processing Configuration
Hierarchical Data Processing with Schema Changes
Intelligent Structure Models
Stateful Computing
Appendix A: Connections
Appendix B: Data Type Reference
Appendix C: Function Reference
- Function Support in a Non-native Environment
- Function and Data Type Processing
  - Rules and Guidelines for Spark Engine Processing

User Guide

10.2.2
- 10.5.7
- 10.5.6
- 10.5.5
- 10.5.4
- 10.5.3
- 10.5.2
- 10.5.1
- 10.5
- 10.4.1
- 10.4.0
- 10.2.2 HotFix 1
- 10.2.2 Service Pack 1
- 10.2.1

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Big Data Process

As part of a big data project, you collect the data from diverse data sources. You can perform profiling, cleansing, and matching for the data. You build the business logic for the data and push the transformed data to the data warehouse. Then you can perform business intelligence on a view of the data.

Based on your big data project requirements, you can perform the following high-level tasks:

Collect the data.

Cleanse the data

Transform the data.

Process the data.

Monitor jobs.

Introduction to Informatica Big Data Management

Step 1. Collect the Data

Step 2. Cleanse the Data

Step 3. Transform the Data

Step 4. Process the Data

Step 5. Monitor Jobs