Semantic Data Conversion for Unified Enterprise Data Display
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Solution Overview
Problem
Existing enterprise data management systems face challenges in efficiently managing large quantities of disparate data from various sources due to their complexity, variability, and poor interoperability, leading to high implementation costs and difficulties in custom-tailored integration.
Innovation Solution
A system comprising a configuration workstation, controller, and web server that converts data from various sources to a semantic data representation, allowing for highly configurable user interfaces, with data validation and role-based access, enabling unified data presentation and insights.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If custom-tailored integration solutions are created for enterprise data management, then data management effectiveness is improved, but implementation cost and system complexity increase
Solution Approach 1:
The patent implements a universal data integration platform that can handle multiple data sources, formats, and integration scenarios through a single standardized system. The platform provides reusable components, templates, and pre-built connectors that work across different enterprise systems, eliminating the need for custom-tailored solutions for each integration project while maintaining high data management effectiveness
Solution Approach 2:
The patent employs copying by creating reusable integration templates, data models, and configuration patterns that can be replicated across different integration scenarios. Instead of building custom solutions from scratch, the system allows users to copy and adapt proven integration patterns, significantly reducing implementation complexity and cost while maintaining reliability
2Reliability
If custom-tailored integration solutions are created, then data management effectiveness is improved, but ease of implementation deteriorates
Solution Approach 1:
The patent applies preliminary action by pre-configuring integration templates, data validation rules, transformation logic, and connection parameters before actual deployment. The system includes pre-built connectors for common enterprise systems, pre-defined data models, and automated configuration workflows that guide users through implementation, making the process straightforward while maintaining effective data management
Solution Approach 2:
The patent implements self-service capabilities through automated data discovery, self-configuring connectors, and intelligent template selection that guide users through integration without requiring deep technical expertise. The system automatically detects data sources, suggests appropriate integration patterns, and handles routine configuration tasks, improving ease of implementation while ensuring reliable data management
3Adaptability or versatility
If data from disparate sources is integrated, then data accessibility is improved, but device complexity increases
Solution Approach 1:
The patent introduces an intermediary layer - a standardized data integration platform - that sits between disparate data sources and user applications. This intermediary handles format conversion, data normalization, and protocol translation, allowing data from diverse sources to be accessed uniformly without requiring complex point-to-point integration logic in the application layer
Solution Approach 2:
The patent applies segmentation by breaking down the integration process into modular, independent components: data source connectors, data validation modules, transformation rules, and presentation layers. Each component handles a specific aspect of integration independently, making the overall system more manageable and less complex while improving data accessibility across multiple sources
Data Source
AI summary
A configuration workstation generates configuration tables representative of applications that each comprise one or more object data structures. Each of the object data structures are linked to one or more staging databases that, in turn, obtain data from one or more standalone data sources. Each of the object data structures comprises at least one property that defines available data for the object data structure. The configuration tables are provided to a controller that obtains data from the staging database(s). The controller also causes the obtained data to be converted to the semantic data format and stored in a semantic database. A web server obtains requested semantic data from the semantic database for at least some of the object data structures for an application. The web server then generates a user interface based on the requested semantic data and provides it to a user device for display.