Unified BI Filtering Across Disparate Analytics Platforms
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Solution Overview
Problem
Existing analytics systems struggle to consolidate and filter data across disparate business intelligence platforms due to differing data parameters, leading to inconsistent and repetitive manual interactions.
Innovation Solution
A unified filtering mechanism that coordinates parameters across multiple BI&A platforms, allowing users to modify filter values consistently and automatically re-render visualizations, using a central control and machine learning to map and mesh data from disparate sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data is consolidated from multiple disparate BI platforms, then data comprehensiveness is improved, but system complexity increases due to differing data parameters and filtering mechanisms
Solution Approach 1:
The patent introduces a unified filtering mechanism as an intermediary layer between the user and multiple disparate BI platforms. This mediator translates user filter selections into platform-specific parameters, automatically coordinating filtering across IBM Cognos, Microsoft PowerBI, Tableau, and other analytics platforms without requiring users to manually adapt to each system's complexity
Solution Approach 2:
The unified filtering mechanism provides a universal interface that works across multiple different analytics platforms simultaneously. A single filter control can apply filtering logic to visualizations from diverse sources with different native parameter systems, making the consolidation process manageable despite the heterogeneity of underlying platforms
2Measurement precision
If manual filtering is performed in each data system visualization, then filtering precision is maintained, but user effort and time consumption increase
Solution Approach 1:
The patent merges multiple separate filtering operations into a single unified filtering mechanism. Instead of requiring users to apply filters independently to each visualization from different BI platforms, the system combines these operations so that one filter selection automatically coordinates across all connected analytics platforms, maintaining filtering precision while eliminating repetitive manual effort
Solution Approach 2:
The system performs preliminary coordination of filtering parameters across all platforms before rendering visualizations. When a user selects a filter value, the system proactively translates and applies this selection to all relevant data sources in advance, preventing the need for users to manually update each visualization and reducing the risk of inconsistencies
3Adaptability or versatility
If separate filtering mechanisms are used for each analytics platform, then platform-specific functionality is preserved, but data consistency deteriorates due to potential filtering inconsistencies
Solution Approach 1:
The unified filtering mechanism implements feedback loops that monitor and coordinate filter state across all connected analytics platforms. When a filter is applied, the system tracks its application and ensures consistent state propagation, detecting and correcting any inconsistencies that arise from platform-specific rendering behaviors
Solution Approach 2:
The intermediary filtering layer preserves platform-specific functionality by translating unified filter selections into platform-appropriate parameters while maintaining centralized control. This allows each analytics platform to render visualizations according to its native capabilities while ensuring all platforms respond consistently to the same user filtering intent
Data Source
AI summary
A system and method for combining data from disparate business intelligence systems and data sources. The method includes aggregating data in real-time across multiple, disparate data platforms of more than one third party, by mapping nonmatching data parameters used in the different platforms to a common data field. The business intelligence systems are queried to identify responsive data fields, which are then meshed in a translation and/or unification module into the common data field for display. The meshing of the data allows for efficient filtering according to user inputs. The system and method further include applications to allow users to create parameter mappings for the data meshing.