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  • Informatica Data Quality 10.4.0
  • All Products

Table of Contents

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  1. Preface
  2. Mappings
  3. Mapplets
  4. Mapping Parameters
  5. Where to Assign Parameters
  6. Mapping Outputs
  7. Generate a Mapping from an SQL Query
  8. Dynamic Mappings
  9. How to Develop and Run a Dynamic Mapping
  10. Dynamic Mapping Use Cases
  11. Mapping Administration
  12. Export to PowerCenter
  13. Import From PowerCenter
  14. Performance Tuning
  15. Pushdown Optimization
  16. Partitioned Mappings
  17. Developer Tool Naming Conventions

Developer Mapping Guide

Developer Mapping Guide

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Mappings Overview

Mappings Overview

A mapping is a set of input and output objects that represent the data flow between sources and targets. They are linked by transformation objects that define the rules for data transformation. The Data Integration Service uses the instructions configured in the mapping to read, transform, and write data.
You can run a mapping from a workflow so that you can run multiple mappings sequentially. Or, you can develop a workflow that runs commands to perform steps before and after a mapping runs. You can include a mapping with physical data objects as the input and output in a mapping task in a workflow.
The type of input and output object you include in a mapping determines the type of mapping. You can create the following types of mappings in the Developer tool:
Logical data object mapping
Links a logical data object to one or more physical data objects. A logical data object mapping helps you to integrate data from multiple sources and formats into a standardized view.
Operation mapping
Has an operation as the mapping input, output, or both. An operation mapping performs the web service operation for the web service client.
Virtual table mapping
Has a virtual table as the mapping output. A virtual table mapping defines the virtual data flow between sources and a virtual table in an SQL data service. Use a virtual table mapping to transform the data.
Dynamic mapping
A mapping in which you can change the sources, targets, and transformation logic at run time based on parameters and rules that you define. Use a dynamic mapping to manage frequent schema or metadata changes.
The following image shows an example of a mapping:
A mapping can contain physical data objects as inputs and outputs and represents the data flow between sources and targets. It can also contain transformations. You can also perform actions, such as validating and running the mapping or include the mapping in a workflow.
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