Business Intelligence Report Trust Aggregation
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Solution Overview
Problem
Current business intelligence data storage and retrieval systems fail to effectively evaluate the trustworthiness of reports, making it difficult to determine the accuracy and freshness of data, which undermines the value of reports due to lack of clear validation and aggregation of trust levels.
Innovation Solution
A system that processes and aggregates trust values based on data currency, quality, certification, and content status to provide a custom measure of report trustworthiness, using metadata to visually represent trustworthiness through icons and configurable weights, allowing users to drill down for detailed criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If data from multiple sources is integrated into reports, then the comprehensiveness and value of business intelligence is improved, but the ability to determine data accuracy and source reliability deteriorates
Solution Approach 1:
The patent segments trust evaluation into distinct components: data source trust values, report trust values, and individual data element trust values. Each component is evaluated and stored separately, allowing traceability back to specific sources while managing complexity through modular evaluation.
Solution Approach 2:
The patent introduces trust values as an intermediary mechanism that mediates between multiple data sources and the final report. These trust values serve as metadata that carry reliability information through the data integration process, enabling source attribution without requiring complex direct tracking of each data element.
2Reliability
If validation metadata is stored for data sources, then data reliability assessment is improved, but the usability and direct application of validation information in report generation deteriorates
Solution Approach 1:
The patent merges validation metadata with the report generation process by automatically incorporating trust values into reports. The validation information is combined with data elements during report creation, making reliability assessment seamless and directly applicable without requiring separate manual evaluation steps.
Solution Approach 2:
The patent implements feedback mechanisms where trust values are automatically calculated based on validation metadata and fed back into the report generation process. This automated feedback loop ensures that validation information is continuously applied and updated, improving both reliability assessment and operational ease.
3Measurement precision
If trust values are aggregated across multiple data sources, then overall report trustworthiness measurement is improved, but the complexity of trust evaluation calculation increases
Solution Approach 1:
The patent performs preliminary evaluation of trust values for individual data sources and data elements before aggregation. By pre-calculating and storing trust values in a structured format, the system prepares the necessary components for aggregation, reducing the complexity of the final calculation while maintaining measurement precision.
Data Source
AI summary
A computer readable medium includes executable instructions to form a report; process trust values, where each trust value characterizes the accuracy of an attribute of the report; combine trust values to provide an aggregate trust value associated with the report; and supply a user with the report and the aggregate trust value.