Data Policy Template

Deprecation Notice (Effective ADOC v26.2.0)

Data Policy Templates have been deprecated as part of a shift toward direct rule-based configurations. Users can continue to implement anomaly detection logic using rulesets, which provide equivalent and more flexible functionality.

A Data Policy Template is a reusable collection of rule definitions that can be applied to multiple Data Quality Policies. Instead of defining rules every time you create a policy, you can create a single template containing multiple rules. When you add this template to a policy, all the rules it contains are automatically evaluated.

Benefits:

Saves time by reusing common rule definitions
Ensures consistency across multiple policies
Simplifies policy creation for new datasets

Adding a Data Policy Template

Follow these steps to create a new Data Policy Template:

Navigate to: Data Reliability > Manage Policies > Data Policy Templates tab.
Click Add Data Policy Template to open the configuration page.
Enter the following details:
- Name: Provide a descriptive name for the template (e.g., Customer Table Quality Rules).
- Description: Explain why this template is being created.
- Select Rules: Choose the rules to include in the template.

Measurement Types and Rule Definitions

Measurement Type	Description	Example
Null Values	Verifies whether selected columns contain null values	Customer email should not be null
Schema Match	Checks if column data types match the expected type	Customer ID must be Integer
Pattern Match	Ensures column values follow a regular expression	Emails must match `^[\w.%+-]+@[A-Za-z0-9.-]+\.[A-Za-z]{2,}$`
Enumerations	Validates values against a predefined list	Status must be `Active`, `Inactive`, or `Pending`
Tags Match	Ensures values are present in a specified tag	Product category must match a defined tag
Range Match	Validates values fall within a lower and upper bound	Order total between 0 and 10,000
Uniqueness Check	Ensures values in a column are unique	Customer ID column must be distinct
Duplicate Row Check	Detects duplicate rows in a dataset	Ensure no repeated transaction records
Row Check	Validates total number of rows falls within a range	Table must have 10,000–12,000 rows
Lookup	Compares values with a reference table or column; optional SQL filter	Check IDs exist in a reference table where `is_active = 'Y'`

(Optional) Add Labels by clicking Add Labels and providing key-value pairs for easier categorization.
Click Save to create the template.

Understanding the Data Policy Templates Table

The Data Policy Templates table provides an overview of all templates you have created. You can search for a template by its name.

Column Name	Description
Name	Name of the data policy template
Description	Description provided when the template was created
Data Dimensions	Lists data dimensions defined in the template (e.g., Consistency, Uniqueness)
Labels	Displays any labels associated with the template
Created At	Date and time the template was created
Updated At	Most recent date and time the template was updated
Vertical Ellipsis Icon	Click to edit or delete the template

Editing a Data Policy Template

Go to the Data Policy Templates tab in Manage Policies.
Click the name of the template you want to edit.
Update the rules, description, or labels as needed.
Click Save to apply the changes.

Example:

You have a template Customer Table Rules with 5 rules.
You add a new Pattern Match rule to check email formats.
After saving, all policies using this template will now automatically include the new rule.

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