Business Intelligence (BI) Testing with Sample Test Cases

What is Business Intelligence Testing?

The process of obtaining, cleaning, analyzing, integrating, and sharing data to derive actionable insights that drive corporate progress is known as BUSINESS INTELLIGENCE (BI). Business intelligence testing, often known as BI testing, evaluates the staging data, ETL process, and BI reports, as well as ensuring proper deployment. Data credibility and correctness of insights derived from the BI process are ensured through BI testing.

This article will teach you more about ETL and Business Intelligence.

The sequence of Business Intelligence Testing

Examine the information at the source

Business data rarely comes from a single source or in a single format. Check to see if the source and the type of data it sends are the same. Also, perform some basic validation right now.

Assume that information on a student is sent from a source for processing and storage. At this step, double-check that the details are correct. If your GPA is a 7, you've certainly outperformed the 5-point system. As a result, such data can be destroyed or updated without having to send it to a third party for further processing.

This is normally the ETL's "Extract" stage.

Make sure the data transformation is correct

This is where raw data is transformed into business-specific information. The data types of the source and destination should be the same. For example, you can't save the date as text.

The primary key, foreign key, null, and default value constraints, among other things, should all be present. The source and destination's ACID properties should be checked, and so on.

Verify that the data is loading

(Into a data warehouse, data mart, or wherever it will be kept permanently) −

The scripts that load and test the data would undoubtedly be included in your ETL testing. However, the data storage system must be checked for the following −

  • Performance − As systems become more complex, relationships arise between various components, resulting in a number of co-relations. This is excellent news for data analytics; but, searches with this level of complexity sometimes take too long to get results. As a result, performance testing is crucial in this situation.

  • Scalability − Data is only going to get bigger, not smaller. As a result, tests must be conducted to determine whether the current system can handle the size of the growing business and data quantities. This involves archival strategy testing as well. Basically, you're putting the decision to the test − "What happens to older data, and what if I need it?"

It's also a good idea to test the system's other capabilities, such as its computing capabilities, failure recovery, error reporting, exception handling, and so on.

BI Report Validation

Finally, there are the reports, which are the final layer of the entire process.

This is referred to as Business Intelligence. However, as you can see from the example above, if your preceding layers are broken, the reports will never be accurate, consistent, or speedy.

Look for the following at this point −

  • The reports that were created and how they could be used in the business

  • The ability to modify and customize the parameters that appear in reports. Sorting, categorizing, grouping, and other similar operations

  • The report's physical look. The readability, in other terms.

  • If the BI elements are BI integrated, an end-to-end test should be performed on the application's relevant functionality.

Sample Test cases

Verification of the ETL

  • Check that data is correctly mapped from the source to the target system.

  • Verify that all tables and their fields have been copied from the source to the target system, and that auto-generated keys have been created correctly in the target system.

  • Make sure there are no null fields.

  • Verify that the data is not garbled or truncated and that the data type and format in the target system are correct.

  • Make sure the destination system doesn't have any duplicate data.

  • Check that the transformations have been applied correctly.

  • Verify the correctness of data in numeric fields and the robustness of exception handling.

Staging Data

  • After implementing filter rules, the record count between the STG (staging) tables and the target tables is the same.

  • For the supplied key combination, insert a record that hasn't been put into the target table.

  • Records should not be copied or sent to target tables if they have already been loaded.

  • When the value columns on day 02 load, update a record for a key.

  • Delete the records in the target tables logically.

  • Process tables loaded values

  • Reference tables loaded values

Data Loading in Business Intelligence

  • Check that the destination and source databases are properly connected and that no access concerns exist.

  • Check the truncate option for a full load and make sure it's working properly.

  • Check the session's performance while loading the data.

  • Look for errors that aren't fatal.

  • Check that the calling parent task can be failed if the child task fails.

  • Check to see if the logs have been updated.

  • Make sure the mapping and workflow parameters are correct.

  • Check that the number of tables in the source and target systems is identical.

  • Compare the stage tables' properties to those of the target tables. They ought to be paired.

Reports from Business Intelligence

  • Date and time are displayed.

  • For important figures, decimal precision is required.

  • Display the number of rows and columns on each page.

  • In the report, there are no free qualities.

  • In the report, how are blank values/data displayed for both attributes and key figures?

  • If appropriate, whether the search for attributes is based on key or key&text.

  • Is the text search function case sensitive (upper, lower, or both)?

BI Testing Strategy

Let's look at the procedure that the testers must take now that we know what to test and what resources to employ for ETL and Data Warehouse testing.

A BI testing project is, after all, a testing project. That implies the standard steps of testing apply here as well, whether you're evaluating performance or functional end-to-end testing −

  • Planning a test

  • Methodology for testing

  • Test design (Instead of simple text, your test cases will be query intensive.) This is the SINGLE most significant difference between traditional test projects and ETL/Data Warehouse/BI testing initiatives.)

  • Execution of the test (Once again, you are going to need some querying interface such as TOAD to run your queries)

  • Defect, reporting, closure, etc.


Business intelligence is a critical component of all business operations. E-commerce, health care, education, entertainment, and every other industry rely on BI to gain a deeper understanding of their business and create a superior customer experience.

We hope that this article provided you with enough knowledge to continue your research into the field of Business Intelligence testing.

Updated on: 17-Aug-2021

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