Continuous Integration for Business Intelligence Artifacts
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Solution Overview
Problem
Traditional business intelligence systems lack predictability and testability, leading to issues such as report specifications failing after metadata changes, loss of previous versions, inability to revert to previous working versions, and lack of visibility into changes and outputs without manual execution of reports.
Innovation Solution
Implementing continuous integration and automatic version control to monitor and verify business intelligence software, metadata models, report specifications, and analysis cubes using an automated agent that executes pre- and post-execution assertions and records versions, ensuring system stability and predictability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual testing and inspection processes are used for report specifications, then flexibility in development is maintained, but system reliability and predictability deteriorate
Solution Approach 1:
The system performs self-testing and self-validation through automated agents that continuously monitor business intelligence artifacts. The automated agent executes pre-execution assertions before changes are applied and post-execution assertions after changes, enabling the system to self-verify correctness without manual intervention while maintaining development flexibility.
Solution Approach 2:
The continuous integration system implements feedback loops where test results from automated assertions are immediately fed back to developers. The system monitors changes to metadata models, report specifications, and analysis cubes, executing relevant test cases and providing feedback on whether changes introduced errors, thereby improving system predictability while preserving adaptability.
2Device complexity
If version control is not implemented, then system complexity is reduced, but information loss and inability to revert to previous versions increases
Solution Approach 1:
The system performs preliminary versioning and snapshotting of business intelligence artifacts before changes are applied. The automated agent captures the state of metadata models, report specifications, and analysis cubes before modifications, enabling automatic rollback to previous working versions if errors are detected, thus preventing information loss without significantly increasing system complexity.
Solution Approach 2:
The continuous integration system creates copies of business intelligence artifacts at different version points. When changes are made to report specifications or metadata models, the system maintains copies of previous versions in a version control system, allowing stakeholders to access and revert to previous working versions without adding substantial complexity to the core system.
3Reliability
If automated continuous integration is implemented, then system reliability and testability are improved, but device complexity increases
Solution Approach 1:
The automated agent implements multiple functions within a single system component. It performs pre-execution assertions to validate changes before deployment, executes post-execution assertions to verify correctness after deployment, maintains version control, and provides reporting. This multi-functionality improves reliability and testability while minimizing the increase in device complexity by consolidating automation tasks into a single universal agent.
4Ease of operation
If manual execution and inspection of reports is required, then ease of operation is maintained, but productivity and time efficiency deteriorate
Solution Approach 1:
The system performs preliminary execution of test cases and validation assertions automatically before report specifications are deployed to production. The automated agent executes pre-execution assertions to check for potential errors before changes are applied, and post-execution assertions to verify correctness, thereby improving productivity without requiring manual re-execution of reports, while maintaining operational simplicity for users.
Data Source
AI summary
A system of developing and monitoring a business intelligence environment that utilizes automatic version control and continuous integration techniques to produce tested, reliable business intelligence. Errors are detected and corrected continuously to reduce the time needed by report authors to locate and correct errors in report specifications, metadata models, analysis cubes, and other business intelligence artifacts. Further, by storing previous versions of the artifacts in the source control system, the artifacts can be updated to accommodate revisions needed by the customers, and if revisions damage other parts of the artifacts the revisions can be undone.