pql-assert

You can write DAX unit tests by loading assertion functions into your semantic model to validate data, calculations, and relationships. This exposes standard 4-column results (TestName, Expected, Actual, Passed) for structured QA workflows.

Validating data integrity in Analysis Services models is best achieved through structured assertion functions that check values, columns, tables, and relationships. This enforces model health and maintainability using best-practice validations.

Yes, you can filter DAX test discovery by environment. The framework supports environment-aware testing, allowing you to execute scalable test management workflows specifically across DEV, TEST, PROD, and ANY contexts.

PQL.Assert works with both Power BI and Analysis Services for model governance. It provides dedicated best-practice checks and comprehensive validations to ensure robust computation accuracy and semantic model health.

Available assertions for testing DAX expressions and table relationships cover a wide range of validations for values, columns, tables, and calculations. These functions enable repeatable QA workflows and structured test discovery.

You need unit testing for Power BI semantic models to validate DAX computations and prevent data quality issues. Standardized assertion functions provide repeatable QA workflows, ensuring model integrity and maintainability across development environments.