BUSINESS INTELLIGENCE (BI) TESTING

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