What is Business Intelligence (BI) Testing?
Business Intelligence (BI) Testing helps companies to make decisions based on hard facts or data to progress deeper and better vision so they can manage it. Business Intelligence (BI) Testing helps to verify the data, format, and performance of the reports, subject areas and security aspects of the BI Projects. Insistence on a thorough BI Testing is key for improving the quality of the BI Reports and user adoption.
How is BI Application Testing done?
Testing BI applications is to achieve credible data. And by making the testing cycle effectively data security can be attained. A complete test strategy is the stepping stone of an effective test cycle. The strategy should cover test planning for each stage, every time the data moves and state the authority of each stakeholder
Data Acquisition during BI Testing
The prime aim of data acquisition is to ensure that all of the data is extracted that needs to be loaded in the target. During the data acquisition, development is important to understand the various data sources, the time boundaries of the data selected and any other special cases that need to be considered.
Data Integration testing of your BI app
Testing within the data integration state is the crux as data transformation takes place at this stage. Once the data is translated, thorough testing needs to be executed to ensure underlying data complies with the expected transformation logic. Business requirements get translated into transformation logic.
Checking the Data at the source for your BI app
Business Data does not come from one source and in one format it is in large data type. Make sure that the source and the type of data that it sends matches. For example, a student’s details are sent from a source for subsequent processing and storage. Make sure that the details are correct. If the GPA shows as 7, this is clearly over than the 5 point system. Such data can be damaged or corrected without taking it for further processing.
End to End Testing of your BI app
End to end testing is needed otherwise we may see issues such as data reconciliation discrepancies, even such as resource contention or deadlocks.
The factor of the data warehouse may be behaving as expected; there is no assurance that the entire system will behave the same. Thus execution and authorization of end-to-end runs are recommended. The end-to-end runs will further help in ensuring the data quality and performance acceptance criteria are met.
A BI application should be thoroughly tested to reap the benefits of Big Data Analytics.
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