Automated Business Intelligence Data Testing System

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Solution Overview

Problem

Conventional business intelligence data testing is tedious, time-consuming, and prone to errors due to manual intervention, inadequate test scenario coverage, and complex query requirements, especially in report testing where changing objectives and various data types pose significant challenges.

Innovation Solution

A system and method for automated business intelligence data testing that generates test cases and SQL scripts based on a data mapping file, performs ETL testing, and compares OLAP cube reports to identify errors, reducing manual intervention and ensuring comprehensive test coverage.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If manual testing methods are used for business intelligence data, then flexibility in handling complex query requirements is maintained, but testing efficiency and productivity deteriorate due to tedious and time-consuming processes

Engineering Contradiction:

Improvetesting efficiencyVSAvoidcomplexity of handling query requirements

Core Design Contradiction:

ProductivityVSEase of operation

Solution Approach 1:

The testing system automatically generates test cases, SQL scripts, and execution plans without requiring manual intervention. The system self-services by parsing data mapping files, identifying test scenarios, and executing tests autonomously, thereby improving productivity while maintaining the ability to handle complex queries through automated intelligence

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual mechanical testing operations with an automated computing system. Instead of manually creating and executing test cases, the system uses computer-based algorithms to generate and execute tests, substituting human effort with automated computational processes that handle complex queries more efficiently

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Reliability

If comprehensive test scenario coverage is implemented, then testing quality and reliability improve, but testing time and resource consumption increase

Engineering Contradiction:

Improvetesting qualityVSAvoidtesting time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system performs preliminary analysis of data mapping files to automatically identify and generate relevant test scenarios before execution. By pre-processing the mapping information and pre-generating test cases, the system ensures comprehensive coverage without requiring extensive manual test design time, thus improving reliability while controlling time investment

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The testing system implements feedback mechanisms where test results are automatically analyzed and used to refine subsequent testing. The system learns from execution outcomes and adjusts test scenario selection, ensuring comprehensive coverage of critical paths while avoiding redundant tests, thereby maintaining high reliability with reduced time consumption

Inventive Principle:

Principle #23Feedback

3Productivity

If automated testing is implemented, then testing speed and productivity improve, but test scenario coverage and accuracy may deteriorate due to inadequate handling of complex queries

Engineering Contradiction:

Improvetesting speedVSAvoidtest scenario coverage accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The patent employs sophisticated software-based test generation algorithms that can analyze complex data mapping relationships and generate appropriate test scenarios automatically. The computational system substitutes manual test design, using structured parsing and rule-based generation to ensure accurate test scenario coverage while maintaining high testing speed

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system introduces an intermediary layer between the data mapping files and test execution. This intermediary component parses mapping information, generates SQL scripts, and creates test cases as an intermediate representation, ensuring accurate translation of complex query requirements into executable tests while maintaining automated processing speed

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS9710528B2System and method for business intelligence data testing

Publication Date: 2017.07.18 WIPRO LTD

AI summary

Apparatuses, methods, and non-transitory computer readable medium for testing business intelligence data over a communication network include receiving a data mapping file, applicable to a source data repository and a target data repository, and generating data mapping file based on the same. Test cases are generated, based on the data mapping file, and SQL scripts, for execution of the test cases, and executing the SQL scripts on the source data repository and the target data. An online analytical processing (OLAP) cube report for the target data repository is received and the OLAP cube report and a report, which is to be tested, are compared to generate a comparison report. The comparison report is indicative of the fields of the OLAP cube report and the report, which is to be tested, which generated at least one error.