Business Intelligence (BI) Testing for Reliable Business Reports

Business owners are responsible for the growth and stability of their business. That is why they carefully take steps while making any kind of decision regarding their business, whether it is about providing valuable insights or making growth strategies based on the data provided in the reports. 

In that case accuracy of reports plays an important role because their decisions depend on the data provided in them. If any of their decisions go wrong because of the flawed data, their business will suffer. 

For that reason, businesses depend on BI testing to make sure that everything in the reports, data models, and dashboards is reliable and accurate. 

It helps business owners to check if everything is aligned with the business requirements.  

What is Business Intelligence (BI) testing?

Business intelligence (BI) testing checks and validates the data pipeline of the BI system, from ETL processes to the final output. 

Companies are able to get their business information in accurate detail, which eventually helps them assess every matter from every aspect. It is the process of gathering accurate raw data and then transforming it into meaningful information, helping businesses make their strategies more effective. 

Business intelligence environments are complicated, so for these end to end robust testing becomes important to provide authentic and current data with AI-driven analytics. 

With time, this testing method has been proven to be very beneficial for business and even individual users as they get clarity about business methods. 

BI testing also improved the quality of software testing tools for a smooth user experience.  

4 Steps of the BI Testing Process

BI testing is the process of verifying data which is used in future to make important business decisions. It is important to make sure if it is accurate and trustworthy. There is a process of business intelligence testing:

1) Verifying the Source Data

The first step is to do basic validation, where they verify the source from which they are getting the data. 

2) Verifying the Transformation of Data: 

The next step is to process raw data into meaningful information, which is known as business-explicit data. Here comes a condition where the source type should be equal to the destination data type. 

Important database rules must not be changed while transferring; the default, foreign key, primary key, and null value should remain the same. While moving data, formatting rules and reliability of the data must be the same. 

There should not be any error in the ACID properties of source and destination data types.

3) Verifying the Data Loading: 

In ETL testin,g we test the data that is being loaded and verify if the data storage system is fast, reliable and able to handle future growth:

4) BI Report Testing

If the initial layers, such as ETL, Data Warehouse, and OLAP, are not functioning properly, then the BI reports are not accurate and reliable. 

Here comes BI Report Testing, where we verify the reports generated by the Business Intelligence system. Mainly, they check how the reports are being used in the business, as they should help in decision-making. 

Secondly, the parameters should be customizable so that we can sort, group or filter them according to our requirements.Confirm if the report’s proper written documentation is available as it is very important. Lastly, make sure that everything is working fine from start to end by testing.

Major Challenges of BI Testing

There are some potential challenges which organisations may face while doing BI testing:

1) BI System Complexity

BI systems handle a huge amount of data coming from different sources. It can be difficult to test this data as it will contain errors, missing values, or duplicate records. These factors affect the accuracy of the BI results.

2) Choosing the Right BI Testing Tools

Multiple tools are available for BI testing but choosing the right one is important. The choice of the tool depends on what type of testing you want to do, like if you want to check data authenticity or just wanting to see how the data behaves inside BI dashboards and analytics.

3) Lack of Responsibility

Testing is a huge responsibility so if there is no specific team that is assigned to do testing, then there can be a lack. It is better to assign this work to a specific team so they can do this task with proper focus.

4. No BI Testing Strategy

You always need a strategy before starting BI testing. A plan should be finalised, including what to test, who will manage the testing, a checklist of quality standards to follow and how often testing will happen. That will make it easy for anyone to follow these steps to perform consistent and reliable testing. 

5. BI/QA Knowledge Gap

There is a lack of skilled BI testers in the market, which makes it difficult for bigger companies to manage their 5-9 BI systems simultaneously. They can get confused in understanding how a BI system works and what needs to be tested in that specific system.

6. Manual BI Testing 

Some businesses also do manual BI testing. It can be slow, full of human errors, and impossible to cover. It is recommended not to just rely on warehouse data testing, as it can have human errors. So it is better to also test with automated BI testing tools.

Advantages of BI Testing

Bi testing has become essential for every business as it comes up with benefits that help businesses grow and scale on a larger scale. Some of the major benefits are:  

1. Better Data & Analytics Quality

BI testing ensures that data does not change during the entire process to avoid any mistakes.  Mistakes. All the data will stay correct and clean at every step, which will help leaders to make smart and accurate decisions.

2. Reduced Risk of Errors

Data will be reliable because of the automated BI testing. That will save leaders from making business decisions incorrectly. 

3. Better Efficiency

While BI testing, you will be able to find the errors that will help you save time, as you will not have to struggle with the wrong information or reports later on. 

4. Builds a Strong Data Culture

When BI testing reduces errors, people trust the dashboards and reports more. This will increase the confidence of the user and will encourage more people to use data for decision-making.

Conclusion

BI testing is necessary for every business to make sure that their data is transformed, processed and reported correctly. 

Genuine and authentic BI testing prevents issues like low data quality. It also makes sure that the system can manage growing data needs. 

When you validate BI reports and check the accuracy of the data through ETL processes, testers get the confidence that businesses can trust the data for making decisions.