Predictive Profile Sharing for Relationship-Based Cross-System Visibility
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Solution Overview
Problem
Existing data systems face inefficiencies in managing large volumes of unstructured data, leading to unnecessary network bandwidth occupation and limited visibility of shared data, particularly in service architectures where output data is transmitted in a single instance and visibility is restricted to the requesting system.
Innovation Solution
A predictive profiling platform that generates multi-dimensional profiles and predictions, enabling coordinated display interfaces across systems based on intelligent data gathering and mapping, allowing shared visibility and authorized user functions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a requesting system dumps a large volume of unstructured data and relies upon the data process to implement sorting, organizing, filtering, and transforming tasks, then the base task can be performed, but network bandwidth is unnecessarily occupied and processing efficiency deteriorates
Solution Approach 1:
The patent applies preliminary action by requiring the requesting system to pre-process and structure data before transmission. The system must organize data according to specified schemas and dimensions prior to sending it to the data process, thereby eliminating the need for network transmission of raw unstructured data and reducing bandwidth consumption while improving processing efficiency
Solution Approach 2:
The patent extracts and separates the data structuring and organization tasks from the core data processing function. By requiring the requesting system to extract and prepare data in the required format before transmission, the patent removes the inefficiency of transmitting and processing raw unstructured data through the network and data process
2Loss of information
If output data is transmitted in a single instance to the requesting system in a service architecture, then the requesting system receives the data, but visibility and use of the output data is limited to the requesting system and network bandwidth is unnecessarily occupied
Solution Approach 1:
The patent applies segmentation by dividing the data distribution function into multiple targeted transmissions. Instead of a single broadcast to all systems, the output data is segmented and selectively transmitted only to those systems that have defined mappings and relationships with the requesting system, thereby improving data visibility where needed while reducing unnecessary network bandwidth consumption
Solution Approach 2:
The patent introduces a mapping/relationship system as an intermediary that determines data distribution. This intermediary layer identifies which systems should receive the output data based on defined relationships, enabling controlled visibility sharing without requiring broad network transmission to all potential systems
3Adaptability or versatility
If the requesting system is responsible for sharing output data with relevant systems for downstream operations, then data can be distributed, but the responsibility lies upon the requesting system and network bandwidth is unnecessarily occupied in redundant sharing
Solution Approach 1:
The patent applies universality by creating a general mapping/relationship framework that enables automated data distribution to multiple systems based on predefined relationships. This multi-functional approach allows the system to automatically determine and share data with any system that has an appropriate mapping, eliminating the need for manual sharing responsibilities while preventing redundant transmissions through relationship-based filtering
Data Source
AI summary
Aspects of the present disclosure provide technical solutions embodied in a predictive profiling platform. In example embodiments, the predictive profiling platform is configured to generate multi-dimensional system profiles and predictions thereof, provide shared visibility of system profiles between systems that are mapped together based on relationships between respective users, and enable improved cross-system functionality and operations.