Comparing to a Defined Rule

Overview

The Validatar platform provides a comprehensive feature for comparing your Test Data Set against a predefined rule, enhancing the data quality checks for your data governance strategy. This process varies based on how the Test Data Set is retrieved — either by a script or by a profile result.

Importance of Data Quality Rules

Implementing data quality rules is a crucial part of data testing and governance. These rules help maintain consistency, ensure accuracy, and promote trust in your data. They provide a benchmark against which to evaluate your data sets, enabling you to identify anomalies, enforce data integrity, and manage data changes. They also provide high value to your organization by setting up checks for vital areas of concern and known data quality issues.

Setting Up Rules for Script-Based Test Data Set

When comparing data pulled using a script, you can set up rules in the following ways:

1. Numeric Range: Define a specific numeric range, and the test will check if the data falls within this range.

2. Numeric Value: Specify a numeric value, and the test checks if the data matches this value.

3. String Value/Pattern: Set a specific string value or a pattern, and the test verifies if the data matches this value or pattern.

4. Date Range: Specify a date range, and the test verifies if the data falls within this range.

5. Date Value: Define a specific date, and the test checks if the data matches this date.

You decide whether to treat Date values as a Date, Date/Time, or Date/Time with Time Zone field. You can also decide if dates are relative or absolute.

Setting Up Rules for Profile Result-Based Test Data Set

When comparing data derived from a profile result, you can set up rules in these ways:

1. Numeric Range: Just like with script-based data, you can define a numeric range that the data should fall within.

2. Numeric Value: Specify a numeric value that the data should match.

3. String Value/Pattern: Set a specific string value or pattern that the data should match.

Using String Value/Pattern Rules

Validatar's String Value/Pattern rule is versatile. You can use it to validate if the data matches a single value or fits a particular pattern via regular expressions. This flexibility allows for complex validations, helping ensure the data's integrity and conformity to specific standards.

Conclusion

By comparing to a defined rule, you can boost your data quality & governance strategy, ensuring the reliability, consistency, and accuracy of your data.