iceDQ for Power BI Testing
Deliver Power BI reports that business can trust.
When reports fail, decisions fail. And let’s be honest—bad data can get expensive fast. So why not test your reports thoroughly before they hit production?
iceDQ brings automated data quality assurance directly into your Power BI development lifecycle. It tests and certifies your semantic models, datasets, dashboards, and reports before they’re deployed—so your business always operates on reliable, validated insights.
Test Power BI Reports Dashboard in iceDQ
iceDQ enables end-to-end validation of embedded Power BI reports and dashboards, ensuring that visualizations accurately reflect the underlying data. The testing workflow includes:
- Embed Power BI reports and dashboards: Securely connect and embed Power BI reports within iceDQ to enable automated validation of the underlying datasets driving your reports and sub-reports.
- Select the subreport for testing: Choose the specific page, tab, or visual within the embedded report that you want to validate.
- Apply dynamic filters: Configure dynamic or parameter driven filters to replicate real user scenarios and validate filtered report outputs.
- Apply data checks on report element: Define and execute data quality checks on tables, charts, KPIs, and other report elements to ensure accuracy, completeness, and consistency.
Test Power BI Semantic Model in iceDQ
iceDQ enables direct validation of the Power BI semantic layer, ensuring that measures, relationships, and model level logic produce accurate and reliable results. The testing workflow includes:
- Connect to the semantic layer: Establish a secure connection to the Power BI semantic model to access tables, relationships, measures, and calculated columns.
- Use DAX queries to select and filter data: Leverage DAX queries to extract, filter, and shape semantic model data for targeted validation scenarios.
- Apply data checks on semantic data elements: Define and execute data quality checks on measures, calculated fields, hierarchies, and other semantic elements to ensure correctness and consistency.
Create Data Reconciliation Rules in iceDQ
iceDQ enables flexible reconciliation across multiple data sources and reporting layers, ensuring that values remain consistent from raw data to semantic models and final reports. The reconciliation workflow includes:
- Semantic data model vs. Database: Compare measures, calculated fields, and model-level outputs against the underlying database tables to validate transformations, relationships, and business logic.
- Report vs. Report: Reconcile values between two reports—across environments, versions, or visualization layers—to ensure consistency in KPIs, aggregates, and displayed metrics.
- Compare data values at row and column level: Perform granular comparisons of row-level records and column-level aggregates to detect mismatches, missing data, or calculation discrepancies.
Create Validation & Checks in iceDQ
iceDQ provides a comprehensive framework for defining and executing validation rules to ensure data accuracy, consistency, and compliance across reports and data models. The validation workflow includes:
- Implement business rules: Define custom business logic to validate data against organizational policies, domain rules, and expected behaviors.
- Validate report attributes: Verify key report attributes such as metadata, filters, parameters, and structural elements to ensure reports are configured correctly.
- Check format: Validate formatting rules—including data types, number formats, date formats, and display conventions—to ensure consistency and usability across reports.
- Validate calculations: Confirm that calculated fields, KPIs, and aggregated values produce correct results by comparing them against expected logic or reference datasets.
PRODUCT HIGHLIGHTS
 | Complete BI- Layer Coverage |  | Automate testing across the entire BI stack, including semantic models, dashboards, and reporting logic. |
 | Embed Reports |  | Shift left with data testing—identify defects early, long before they reach business users. |
 | No-Code Testing |  | Eliminate scripting. Build and execute tests with just a few simple clicks. |
 | DAX Support |  | Natively run DAX queries for precise validation of semantic model logic. |
Automate your Power BI Report
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FAQs: Power BI testing with iceDQ
What types of Power BI connectivity are supported by iceDQ?
iceDQ supports connectivity to Power BI through the XMLA endpoint and Power BI Embedded services, enabling access to reports, datasets, and underlying semantic model data.
Can iceDQ access data from the Power BI semantic layer?
Yes. iceDQ can retrieve data directly from the Power BI semantic layer using XMLA endpoint APIs, including full access to datasets, tables, measures, and relationships.
Does iceDQ support DAX queries?
Yes. iceDQ provides native support for DAX queries through its DAX query DSL, allowing precise extraction and validation of semantic model data.
Can iceDQ use Power BI parameters for testing?
Yes. iceDQ can pass dynamic parameters at runtime to modify data source connections or apply filters. This enables scenario based testing and validation using runtime filters.
Does iceDQ support testing of Power BI Dashboards, Reports, and Paginated Reports?
Yes. iceDQ supports automated testing of Power BI Dashboards, Reports, Paginated Reports, and the semantic layer.
Can iceDQ compare a BI report with another reporting tool?
Yes. iceDQ can compare Power BI reports with reports from other BI platforms. A full list of supported connectors is available within the product documentation.
Can iceDQ compare cloud based BI reports with on-premises databases or files?
Yes. iceDQ can connect to both cloudbased BI platforms and on-premises databases or files, enabling crossenvironment reconciliation and validation.