Business Intelligence (BI) Testing: Process and Strategy

In this article, we have provided a detailed explanation of the process of testing business data. Let’s understand the steps to business intelligence.

Business Intelligence (BI) is a process of gathering, analyzing, and transforming raw data into accurate, efficient, and meaningful information which can be used to make wise business decisions and refine business strategy.

BI gives organizations a sense of clairvoyance. Only perception is not fueled by extra-sensory ability but by facts.

Business Intelligence testing initiatives help companies gain deeper and better insights so they can manage or make decisions based on hard facts or data.

Steps to Business Intelligence

The way this is done has changed considerably in the current day’s market. What used to be offline reports and such is now live business integration.

This is great news for both businesses and users because:

• Businesses know what is working and what is not easy
• Better User experience with the software

Recommended read => Business Process Testing (BPT)

BI cannot be achieved with one tool or via one system. It is a collection of applications, technologies, and components that make up the entire implementation.

To simplify and show you the flow of events:

User Transactional Data (Relational Database, or OLTP) Flat files, records or other formats of data etc. -> ETL processes-> Data Warehouse->Data Mart->OLAP additional sorting, categorizing, filtering, and providing meaningful insights – BI.

Business Integration is when these analytics affect the way a certain application works.

For example, your credit card might not work at a new location because BI alerts the application that it is an unusual transaction. This has happened to me once. I was at an art exhibition where there were artisans from different parts of the US. I used my credit card to buy a few things, but it would not go through because the seller was registered from a part of US that my credit card was never used at. This is an example of BI integration to prevent fraud.

Recommended products on Amazon and other retail sites, related videos on video sites etc. are other examples of Business Integration in BI.

Based on the above flow, it is also apparent that ETL and storage systems are important for successful BI implementation. Which is why BI testing is never an independent event. It involves ETL and Data warehouse testing as integral elements. As testers, it is important to understand and know more about how to test these.

STH has you covered there. We have articles that talk about these concepts. I will provide the links below so we can get those out of the way and focus on BI alone.

• ETL Testing / Data Warehouse Testing – Tips, Techniques, Processes and Challenges
• ETL vs. DB Testing – A Closer Look at ETL Testing Needs, Planning and ETL Tools

One more thing that Business Intelligence testing experts almost always recommend is: Testing the entire flow, right from when the time data gets taken from the source all the way to the end. Do not just test for reports and analytics on your end alone.

Therefore, the sequence should be:

Business Intelligence Testing Sequence

#1) Check the Data at the source

Business Data usually does not come from one source or in one format alone. Make sure that the source and the type of data that it sends matches. Also, do some basic validation right here.

Let’s say one student’s details are sent from a source for subsequent processing and storage. Make sure that the details are correct, right at this point itself. If the GPA shows as 7, this is clearly more than the 5 point system. Such data can be discarded or corrected right here itself without taking it for further processing.

This is usually the “Extract” stage of the ETL.

#2) Check the data transformation

This is where the raw data gets processed into business targeted information.

• The source and destination data types should match. E.g.: You can’t store the data as text.
• Primary key, foreign key, null, default value constraints, etc. should be intact.
• ACID properties of the source and destination should be validated, etc.

#3) Check the data Loading

(Into a data warehouse, Data mart, or anywhere it is going to be permanently located):

The actual scripts that load the data and test them will definitely be included in your ETL testing. The data storage system, however, has to be validated for the following:

• Performance: As systems become more intricate, there are relationships formed between multiple entities to form several co-relations. This is great news for data analytics, however, this kind of complexity often results in queries taking too long to retrieve results. Therefore, performance testing plays an important role here.
• Scalability: Data is only going to increase, not reduce. Therefore, tests have to be done to make sure that the size of the growing business and data volumes can be handled by the current implementation or not. This also includes testing the archival strategy as well. Basically, you are trying to test the decision- “What happens to older data and what if I need it?”

It is also a good idea to test the other aspects such as its computational abilities, recovery from failure, error logging, exception handling, etc.

#4) BI Report Testing

Finally, the reports, the last layer of the entire flow.

This is what is considered Business Intelligence. But, as you can see from the above, the reports are never going to be correct, consistent and fast if your preceding layers were malfunctioning.

Further Reading => Best BI Consulting Companies in the Market

At this point, look for:

• Reports generated and their applicability to the business
• Ability to customize and personalize the parameters to be included in the reports. Sorting, categorizing, grouping, etc.
• The appearance of the report itself. In other words, the readability.
• If the BI elements are BI integrated, then the corresponding functionality of the application is to be included in an end-to-end test.

BI Testing Strategy

Now that we know what to test and resources for ETL and Data Warehouse testing, let’s look at what processes the tester needs to follow.

Simply put, a BI testing project is a testing project too. This means the typical stages of testing are applicable here too, whether it is the performance you are testing or functional end to end testing:

• Test planning
• Test strategy
• Test design (Your Test cases will be query intensive rather than plain text based. This is ONE major difference between your typical test project and an ETL/Data Warehouse/BI testing project.)
• Test execution (Once again, you are going to need a querying interface such as TOAD to run your queries)
• Defect reporting, closure etc.

Conclusion

Business Intelligence is an integral element of all business areas. E-Commerce, Health Care, Education, Entertainment and every other business relies on BI to get to know their business better and to provide a killer experience to their users.

We hope this article gives you the necessary information to explore the Business Intelligence testing area much further.

About the author: This post was written by STH team member Swati.

Are you a BI tester? Please do share your experiences, feedback and questions in the comments section below. We would love to hear from you.