Software Testing - Business Intelligence (BI) Testing with Sample Test Cases

The BI Testing is a process of verifying and validating the accuracy, reliability, and performance of the BI System, and reporting the data-driven information for decision-making.

What is Business Intelligence (BI) testing?

Business Intelligence (BI) testing is a process of making sure that data is accurately collected, transformed, and reported within a BI system.

The goal is to verify that the data generated by BI tools is correct, reliable, and useful. BI testing looks at different stages of data handling, like extracting it from sources, transforming it for analysis, and loading it into databases.

Read More: Business Intelligence (BI)

Process of BI Testing

BI testing is all about verifying that the data we rely on for making important business decisions is accurate and trustworthy. The testing sequence of Business Intelligence is:

1. Verify the Source data: Business Data generally doesn’t come from one source and in a single format. Ensure that the source and the kind of data that it sends match. Basic validation is done here.

2. Verify the transformation of data: This is the place where raw data is processed into business-explicit data. The source and destination data types should be equal. The primary key, foreign key, default, and null value have to be untouched. ACID properties of source and destination data types have to be verified.

3. Verify the data loading: The data that is being loaded and tested by the scripts are added for the ETL testing. The data storage system should be verified for the accompanying:

• Performance: For complex systems, connections emerge between different parts of the systems forming various co-relations.  Though it is good for data analytics still a lot of time is required to retrieve data. Therefore performance testing is the major factor.
• Scalability: Data is increasing day by day. Therefore testing of the data is required to decide if the current implementation can handle the data of the increasing business volume or not.

4. BI report testing: This is the thing that is viewed as Business Intelligence. Note that if the previous layers are broken, the reports won’t ever be exact, reliable, or rapid.

The important points are:

• The utilization of the reports that are created for business.
• The parameters that are mentioned in the reports should be modified and customized like sorting, grouping, categorizing, etc.
• The presence of the actual report i.e. the documentation.
• The comparing use of the application is to be included in an end-to-end test if the elements of business Intelligence are integrated together.

Sample Test Cases for BI Testing

Here are some sample test cases to check the main parts of a Business Intelligence (BI) system:

1. ETL Verification Test Cases:

• Verify Data Mapping: It verify that the data is correctly mapped from the source system to the target system.
• Verify Table Copy: Check if all the tables and fields are copied accurately, and confirm that auto-generated keys are correctly set up in the target system.
• Check Null Fields: Make sure there are no unnecessary null fields in the target system.
• Verify Data Integrity: Confirm that the data is intact and not corrupted or cut off. Also, check that the data type and format in the target system match what’s expected.
• Check Data Duplicity: Verify that no duplicate data exists in the target system.
• Verify Transformations: It verify that the required data transformations (like formatting or calculations) have been correctly applied.

2. Staging Data Test Cases:

• Reconciliation Check: After applying filter rules, check that the record count between the staging tables and target tables is the same.
• Check Non-Loaded Records: Insert a record into the staging table and make sure it doesn’t load into the target table if it doesn’t meet the set criteria.
• Verify No Duplicates: It verify that previously loaded records aren’t duplicated during subsequent loads.
• Update Data After Load: If a record’s key value changes, verify that it updates correctly when new data is loaded.
• Logically Delete Records: Check that deleted records are properly marked in the target tables, even if they aren’t physically removed.

3. Data Loading Test Cases:

• Database Connectivity: It verify there are no issues connecting the source and destination databases.
• Truncate Option Validation: For full data loads, verify that the truncate option works properly to remove old data before loading new data.
• Performance Check: Test the performance of the system during data loading to make sure it handles large amounts of data without slowing down.
• Handle Errors Gracefully: It verify that non-fatal errors (like minor glitches) are logged correctly and don’t disrupt the overall process.
• Mapping and Workflow Validation: Check that the mapping and workflow settings are correct during data loading.
• Verify Table Consistency: Compare the number of tables and data structures between the source and target systems to verify everything matches up correctly.

4. BI Report Validation Test Cases:

• Date and Time Display: It verify that dates and times are shown correctly in the reports.
• Decimal Precision: Verify that key figures are displayed with the right decimal precision, especially when dealing with financial or numerical data.
• Row and Column Count: Make sure the reports display the correct number of rows and columns per page.
• Display of Blank Data: Check how blank or null values are handled in the report and verify that they follow the business rules for display.
• Search Functionality: Test the search feature in the reports to make sure it works as expected, whether it's case-sensitive or case-insensitive.

BI Testing Strategy

BI testing follows a regular testing lifecycle but with a special focus on verifying the data accuracy and reliable reporting. Here is a simple guide to structuring your BI testing:

Learn more: Testing Techniques

1. Test Planning: First, define what you're going to test. Identify the key business processes that will be impacted and select the right tools for your testing.

2. Testing Methodology: You'll use two main types of testing here: functional and non-functional. Functional testing checks if the data is correct and consistent, while non-functional testing focuses on things like system performance and how well it can handle larger data sets.

3. Test Design: Next, design your test cases. Focus on the data extraction, transformation, and loading (ETL) process, as well as making sure the reports are correct.

4. Test Execution: Run the tests using tools like TOAD or SQL Server to check if the data and reports are as expected. As you test, document your results carefully, noting any issues that come up.

5. Defect Reporting & Closure: If you find any defects, log them and work on fixes. After the fixes are applied, re-test to ensure everything is working smoothly and as expected.

Conclusion

BI testing is essential for making sure that data is processed, transformed, and reported correctly. By checking the accuracy of the data through ETL processes and validating BI reports, testers ensure that businesses can trust the data for making decisions.

Good BI testing helps avoid issues like bad data quality and ensures the system can manage growing data needs.