Preface
Introduction
- Overview
- Prerequisites
IDD Concepts
Implementation Process
IDD Configuration Manager
Manual IDD Configuration
IDD Global Properties
- Informatica Data Director Global Properties Reference
- Updating the Global Properties
Sizing and Platform Requirements
Application Components
- Application Components Reference
IDD Security Configuration
- IDD Security Configuration Reference
Data Security
- Data Security Overview
- Apply Data Security
Example Role-Based Security Configuration
Data Masking
Siperian BPM Workflow Engine
Locale Codes
- Language Codes
- Country Codes
Troubleshooting
Glossary
- Glossary of Terms

Data Director Implementation Guide

10.3

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Validation

A cleanse function can be used to perform custom data validation.

Validation results are processed if the cleanse function has a validationStatus output parameter.

If the validationStatus parameter is blank, there are no validation errors and the process can continue.

If there are validation errors, the validationStatus parameter will include a series of validation messages describing the inputParameter name and a message. In the IDD application UI, each validation error is associated with an input value in a specific input column.

The Resource Kit contains the ValidationCleanseLib sample, which provides an example of a cleanse library with functions that perform validation in an IDD application.

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Table of Contents

Data Director Implementation Guide

Data Director Implementation Guide

Validation

Validation