Power BI testing is often neglected part of numerous BI dashboards and reports implementations.
The reason behind it is the fact that it is not as glamorous and headline-grabbing as creating a data model, implementing row-level security, verifying access levels, or developing data visualizations in Power BI reports and dashboards. Nonetheless, it is a vital element of any software development implementations.
Business Intelligence projects are no different.
Truth be told, if you don’t perform testing, you risk that your BI dashboards or reports display corrupt information. In such cases, whole implementation makes no point, and the outcome is that you have wasted a lot of time developing it and nobody can use it.
Once you read this article, you will know:
- what does BI report testing include,
- why Power BI testing is important,
- what types of Power BI testing should be performed,
- what are some examples of test cases that can be used to test Power BI,
- how to automate Power BI testing with BI tools.
What does BI report testing include?
Business Intelligence testing allows business users to test, validate and verify the accuracy of the BI reports, BI dashboards, data layer and metadata.
The basic principle for the testing is quite simple – just confront the expected and actual result.
The BI testing strategy you adopt should consist of several simple steps. Let’s look at them to better understand it and better prepare for end-to-end testing of most BI tools.
Step 1: Check the data source.
These days data source usually encompasses not a single source in a single format, but multiple sources with multiple formats. As a result, it is crucial to perform the initial base validation here and verify that the source data and the data type are in accordance.
Step 2: Check the data transformation layer.
It is the place where data is processed into the destination information of the business. Therefore, the source data and target data should match.
Step 3: Check the data loading.
Next step is to verify that the data scripts load data into the testing area, like a testing workspace in Power BI service, correctly. You should also validate the data storage system for performance and scalability.
Performance testing is essential where the changes of obtaining better results exist. Scalability is crucial as it is important to test that it compensates with the growing business needs. This type of verification also helps determine whether these data volumes can be handled well or not.
Step 4: Power BI report testing.
Finally, you can start Power Bi testing running different types of tests for validation. It is advisable to first create thorough test plans to run and then, one-by-one, validate them by checking the functionalities of the report.
Power BI report test plans can entail fully manual testing, semi-automated or automated. Before we dive into each of these, let’s check why bother to Power BI testing anyway and what categories of testing you should include in the testing phase.
Why Power BI testing is important?
Microsoft Power BI is one of the most popular Business Intelligence tools nowadays. More and more companies notice the need for developing advanced analytical solutions to use available data to their advantage and improve decision-making process. Therefore, the accuracy of report data is the key factor in the process.
Consequently, Power BI testing should always be a critical component of the BI software development process. The reasons behind this include, among others:
- Ensuring data accuracy to prevent errors in the data to lead to incorrect results. Testing will prove that the data used in reports is accurate and reliable and there is no issues with BI cache.
- Improving performance to identify performance issues such as slow loading times in case of concurrent user load, or resources constraints,
- Enhancing user experience by making dashboard published in Power BI service more intuitive, easy-to-use, and compliant with the needs of end users. All of these is achieved by testing the functionalities of visual data (for example compare visual data on different pages of the reports), interactions and drill-downs.
- Increasing reliability by identifying issues that may negatively affect the reliability of reports such as data inconsistencies, security vulnerabilities (for example testing different user logins) or system failures.
As you can see, Power BI testing process is essential to ensure that report data is accurate, boost performance of your BI reports, enhance user experience, or increase reliability right from the start of user adoption. As a result, organizations can be sure that they get the most value from the data in BI solutions and are able to make educated strategic decisions. If you want to read more about why is Business Intelligence important for companies, you can do this here.
What types of Power BI testing should be performed?
Truth be told, Power BI testing is such a big topic, that the best approach to tackle it is to split it into different categories. Being aware of them will also allow you to automate the testing process in the next step.
Some of the most Power BI testing categories include:
- Functional testing.
- Regression testing.
- Security testing.
- Performance and stress testing,
- Tolerance testing.
Keep in mind though that there are also compatibility, integration or adhoc report testing, but in this article we will just focus on the mentioned above.
Functional testing encompasses checking the basic functionalities of Power BI reports and dashboards. When you perform functional testing, you check whether the report works as expected and it displays correct values.
For example, a functional can be checking the cross-filtering functionality in the reports. Another example would be to verify that all pieces of visual data load effectively and show correct values, for example in accordance with ODBC enabled data source.
BI tools like Power BI are such popular these days as they provide business users with the ability to analyze and interpret vast amounts of data quickly and efficiently, helping them make more informed and data-driven decisions.
One of its qualities is the possibility to build reports by automatically creating the database queries. They are usually based on predefined data models. The challenge emerges through regression testing as any little change to the BI model will heavily impact the BI reports.
As a result, regression testing in Power BI is the process of testing two versions of the same report, dashboard, or visualization (for example one that dates to previous month and one for current month) to ensure that any changes made to the system or underlying data sources have not caused any unintended effects or introduced any new defects.
A great example of regression testing is cross-environment testing which compares one or more BI dashboards in a specific environment to the same dashboards in another (for example compare visual data in development and production environment).
Just like web applications, Business Intelligence apps also encompass authentication of user logins and authorization of security needs. Numerous Microsoft Power BI apps integrate or embed with other transactional apps. As a result, it is coming to the forefront to also test the security of BI apps.
Security testing should entail testing:
- Report access security – verifying that the access of any BI reports published in Microsoft Power BI Service by certain individuals, departments, or group of individuals.
- Data security – verifying that the report will be different for different people using the report (for example by row-level security feature).
- Single sign-on security – verifying that a single person is authorized to get access to reports in a large enterprise.
Performance and stress testing
These concepts may seem similar, but there is a difference between these two.
Performance testing allows you to evaluate performance of several Microsoft Power BI reports and dashboards. For example, you can check how long one single functional task takes.
On the other hand, performing a stress test enable you to drive load to your server and check the response time or availability. With stress testing you can verify what infrastructure is needed to run it or what is the sustainability at peak concurrent users load. Therefore, stress testing is testing the analytics platform itself and instead of a specific report or dashboard.
Finally, the last type of tests we will go through in this article is tolerance testing. It simply ensures that business users get notification in case of:
- an error in any of their own report or dashboard created in BI platform,
- a KPI violates its threshold value in their own reports,
- a metric or specific data goes outside the margin of error.
Therefore, this type of testing checks the functionality of alert systems and guarantee that the data in Power BI reports and dashboards is in acceptable ranges.
What are some examples of test cases that can be used to test Power BI?
As you can see, there is a large pool of testing categories you can use to check Power BI implementations. For each of these categories you can create numerous tests in your test plans.
Nevertheless, the types of tests or level of detail should you aim at when you start to write them down, depends on the BI implementation itself. It is also worth mentioning that in some cases of business intelligence implementations, not all testing categories may be needed. For example, regression testing won’t find application in brand-new reports where tests should focus on the functionality and performance context.
Therefore, among others, you should take into consideration:
- project objectives and requirements,
- data integration sources,
- expectations of end users.
It is worthwhile then to check with the stakeholders of a Power BI report or dashboard, whether the test plans you have prepared make sense. Their suggestions will allow you to refine them and add new ones to deliver end-to-end testing. It will help you test the implementation thoroughly and ensure that the most critical elements of the report work as expected.
Examples of Power BI test cases
To get you inspired, let’s check some of the basic Microsoft Power BI tests that can help you get started with your testing process:
|Feature||Test case description|
|Data accuracy||Data displayed in the report is accurate and matches the expected results.|
|Filter functionality||Data can be filtered based on different criteria and all the filters work as expected.|
|Sorting functionality||Data can be sorted in ascending or descending order based on different columns.|
|Visualization accuracy||Visualizations in the report are accurate and convey the intended information correctly.|
|Export functionality||Data can be exported in different formats, such as CSV or PDF, and is displayed correctly.|
|Cross-filter functionality||Data is filtered correctly across different visualizations in the report.|
|User permissions||Report is accessible only to authorized users and that different users have different levels of access based on their permissions.|
|Report performance||Analyzing the time taken to load the report and the time taken to generate different visualizations in the report.|
|Data source connectivity||Report is still able to connect to the data sources (for example ODBC enabled data source) and that the connection details have not changed.|
|Report interactivity||Interactive elements of the report, such as slicers, still work as intended.|
|Performance testing||Report’s performance under various conditions, such as increased data volume or user load.|
|Report rendering||Report still renders correctly on different devices, screen sizes, and resolutions.|
|Drill-through functionality||Drill-through functionality is still working as expected and that the data is displayed correctly at each level of detail.|
|Role-based access||Access to reports and source data is restricted based on predefined roles, such as viewer, editor, or administrator (implemented for example by row-level security).|
|Data protection testing||Data transmitted and stored by Power BI is protected using appropriate encryption and security protocols.|
|Compliance testing||Power BI complies with relevant security and privacy regulations, such as GDPR or HIPAA.|
|Data masking testing||Sensitive data is properly masked or redacted in reports and visualizations to prevent unauthorized access or data leaks.|
|Data volume testing||Report or dashboard with a large dataset to determine how well it can handle large amounts of data.|
|Concurrent user testing||Report or dashboard with multiple users accessing it simultaneously to determine how well it can handle concurrent requests.|
|Query response time testing||Report or dashboard with complex queries to determine how well it can handle complex queries and how long it takes to return the results.|
|Load testing||Report or dashboard under a heavy load to determine how well it can handle heavy traffic (concurrent user load) and how it performs under stress.|
|Data refresh testing||Report or dashboard to ensure that it can handle data refreshes without affecting performance and different type of refresh works as expected (for example incremental refresh, or refresh through Power Automate).|
|Measures testing||Measures in the report are correct and display correct data.|
|Visualization performance testing||Report or dashboard with complex visualizations to determine how well it can handle complex visualizations and how long it takes to render them.|
How to automate BI Testing with BI tools?
Once you have prepared tests, it is about time to start testing. As it was outlined in the step 4 of the process, you can perform manual testing, semi-automated and automated test instances.
Although user experience or usability testing is better to be performed manually. Nonetheless, most of the functional tests, stress test or regression testing can be executed automatically. And it comes with a lot of benefits.
Why to automate testing of BI reports?
Automated test cases:
- increase efficiency as automated tests run faster than manual testing process,
- ensure consistency of testing,
- reduce costs by reducing the amount of time and resources needed to execute tests,
- increase test coverage by running many tests quickly,
- detect bugs early,
- don’t carry the risk of human errors,
- have high scalability and repeatability for other BI implementations,
- provide detailed documentation on testing,
- allow employees to save time for more creative tasks.
Although there may be tests that you prefer to run manually (for example, to feel like in the shoes of end users), but Power BI testing automation should also be on your mind. If you automate most of test instances, you can save a lot of time for more creative tasks than compare visual data on different pages of the same report, and you will be able to test more with automatic process than manual testing.
What BI tools can you use to automate Power BI testing?
Nevertheless, to automate Microsoft Power BI testing, you need appropriate software and BI tools that will help you in this mission.
Truth be told, there is the selection of software solutions you can use to test Power BI reports, dashboards, and applications is not very extensive. Most BI tools you can use for testing outlined below were not specifically created to test a BI platform, so you can use them also for other types of software.
It is because the awareness of importance of BI testing is still growing but has not fully matured yet. As a result, the testing phase in BI implementations is still often neglected. Luckily, the BI tools that are already on the market should be sufficient to implement Power BI end-to-end testing automation in your business intelligence projects.
Source: DAX Studio | DAX Studio
DAX Studio is an open-source tool primarily used for writing, analyzing, and optimizing DAX (Data Analysis Expressions) queries in Microsoft Power BI, Analysis Services, and Power Query environments. While not a dedicated testing tool, it indirectly supports to automate Power BI testing by offering the following features:
- query editor – writing and editing DAX queries with IntelliSense support and syntax highlighting (suggesting prompt values and names of measures/tables),
- performance analysis – analyzing and optimizing DAX query performance with detailed metrics and server timings,
- query tracing – capturing and analyze query traces to identify bottlenecks and improve performance,
- exporting data – extracting data from Power BI data models for external validation or further analysis,
- metadata exploration – browsing and examine the structure of your Power BI data models,
- code formatting – applying consistent formatting to your DAX code for better readability and maintainability.
DAX Studio helps to enhance the performance and reliability of Power BI reports and dashboards by optimizing DAX queries and providing insights into data models.
If you read more about automation testing in DAX studio, or start testing, I highly recommend to read this article.
BI Validator from Datagaps
BI Validator is a powerful automated testing tool specifically designed for Power BI and other business intelligence platforms.
The BI Validator offers capabilities such as:
- report comparison,
- data validation,
- performance and stress testing,
- functional and regression testing,
- no-code solution,
- ad-hoc reporting.
What is more, it has a user-friendly interface simplifies test creation and management. If you want read more about BI Validator, you can check it out and request a demo here.
Source: Home | QuerySurge
Query Surge is a data validation and testing solution designed for data-driven environments like Microsoft Power BI. Although the tool was not specifically built for Power BI, it can be used for testing and validating data pipelines feeding into Power BI reports and dashboards.
Its key features include:
- data validation – comparing data source and target data to ensure accuracy and completeness.
- automation – automating testing and validation processes to reduce manual testing effort and human errors,
- test management – scheduling, monitoring, and managing test executions with an intuitive interface,
- root-cause analysis – identifying data issues with drill-down capabilities to find discrepancies.
- continuous integration – connecting to various data sources, including those used by Power BI, to validate data transformations.
QuerySurge provides end-to-end testing experience, ensuring data quality throughout your data pipeline, which in turn enhances the reliability of your Power BI reports and dashboards. If you want to find out more about QuerySurge, request a demo, or try it for free here.
Wiiisdom is an AI-powered Power BI governance tool that helps users manage and maintain their Power BI environments. In fact, it is not a dedicated testing tool, but Wiiisdom supports the overall quality of Power BI reports and dashboards through various features:
- documentation – automatic generation and documentation maintenance for your Power BI artifacts
- data lineage – data flows visualization from sources to reports to understand dependencies and impacts, or dimension attributes of various business objects,
- best practices – evaluating Power BI implementations based on recommended best practices and guidelines,
- AI-driven insights – discovering optimization opportunities and receive recommendations for improving your Power BI reports and data models,
- security – analyzing and monitoring user access, permissions, and data usage to ensure compliance with security policies,
- collaboration – facilitating collaboration among team members with centralized management and reporting.
If you want to read more about Wiiisdom, you should check out their site.
Power BI Sentinel
Power BI Sentinel is a cloud-based service for managing and monitoring Power BI environments. While not primarily a testing tool, it offers features to help maintain the quality of your Power BI reports and dashboards. Its key features include:
- change tracking – monitoring changes in your report, dashboard, and physical data model to identify unintended modifications on business objects,
- automated backups – scheduling regular backups of your Power BI artifacts to prevent data loss,
- data lineage – visualizing data dependencies across reports, datasets, and data sources for impact analysis,
- documentation – generating comprehensive documentation for your Power BI assets,
- security – monitoring user access and report data usage to ensure compliance with security policies.
Although Power BI Sentinel can significantly help you in managing your Power BI environment, it may be not sufficient for in-depth testing of your BI implementation.
Selenium has also not been specifically created for Power BI testing and its focus is automating web applications for testing purposes. Nevertheless, you can automate your testing of Power BI with Selenium as well.
If your BI solution is based on a data warehouse that reports pulled data from and filtered or aggregated before displaying, you can use Selenium to build a test framework to test both the data warehouse and Power BI charts. Selenium will pull data from the charts and compare them to the result of SQL query against the data warehouse.
Although it may be challenging at first as you need to figure out how to scale it as the number of tests grow. Nevertheless, Selenium is an option, and you can use it for your testing automation needs.
All in all, Power BI testing is an essential phase of Power BI implementation. It will validate the accuracy of the BI implementations and ensure that the report or dashboard work as expected. With implementing testing automation with one or more of the above BI tools, like BI Validator, Selenium, or DAX Studio, the whole testing process can go smoothly and increase the quality of your BI project.
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