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
Appendix A: Sizing and Platform Requirements
Appendix B: Application Components
- Application Components Reference
Appendix C: IDD Security Configuration
- IDD Security Configuration Reference
Appendix D: Data Security
- Data Security Overview
- Apply Data Security
Appendix E: Example Role-Based Security Configuration
Appendix F: Data Masking
Appendix G: Siperian BPM Workflow Engine
Appendix H: Locale Codes
Appendix I: Troubleshooting
Appendix J: Glossary
- Glossary of Terms

Data Director Implementation Guide

10.5

Back Next

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.

Rename Saved Search

Table of Contents

Data Director Implementation Guide

Data Director Implementation Guide

Validation

Validation