Author: Kira Wagner, Product Manager at Anaplan.
Data Validation Rules for ADO Pipelines: Feature Overview
We are continuously expanding the pipeline functionality in Anaplan Data Orchestrator (ADO) to provide users with greater flexibility and control over their data integration processes. One of the recent additions is Data Validation Rules, which enable you to validate data directly within your pipelines before it reaches Anaplan datasets, models, or external systems. With 16 available validation rules, you can perform a wide range of checks, including null checks, data type validation, pattern matching, length validation, and value and range checks.
Figure 1: ADO pipeline with a data validation node
These rules help you identify invalid or inconsistent data early in the process, reducing the risk of data quality issues affecting downstream systems. You can also configure how validation failures are handled by choosing to remove invalid rows, log warnings, or stop pipeline execution. Additionally, configurable tolerance limits allow you to define acceptable thresholds for validation failures, giving you greater control over how your pipelines behave when data quality issues are detected.
Figure 2: Configuration of a data validation rule in an ADO pipeline
Figure 3: Execution results of an ADO pipeline with a data validation rule
What you’ll find in the Data Validation Guide
To help you explore and implement this functionality, we’ve created a Data Validation Guide that provides a detailed overview of all 16 available validation rules, including descriptions and practical examples illustrating how each rule can be applied in different scenarios.
The guide also includes step-by-step instructions for adding validation steps to both new and existing ADO pipelines, configuring rules for individual columns, and defining appropriate actions when validation checks fail. You’ll also learn how to configure tolerance limits based on either the percentage or number of failed records, giving you greater control over pipeline execution. Whether you’re setting up data validation for the first time or looking to enhance your existing pipelines, the guide provides the information and examples you need to get started.
Next steps
Interested in learning how to configure data validation rules in your ADO pipelines? Explore the full Data Validation Rules Guide to discover all 16 available rules, understand how they work, and follow step-by-step instructions for adding validations to your pipelines.
