Canonical Model for Enterprise Data Schema Standardization
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Solution Overview
Problem
In corporate environments, data and information often face inconsistencies, duplication, and corruption when transitioning between applications with different schemas, especially when legacy systems are involved, hindering seamless communication and efficient product development.
Innovation Solution
A canonical model is introduced, defining a standardized schema that represents data entities and their relationships as a logical data structure across the enterprise, enabling seamless communication and transformation of data between applications, with a validation module ensuring compliance and a transformation module handling legacy systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is translated between different schemas to enable communication between applications, then data exchange between applications is enabled, but data inconsistencies, formatting issues, duplication, and corruption occur
Solution Approach 1:
The patent introduces a canonical model as an intermediary standard schema that mediates between different application schemas. This canonical model serves as a common reference framework that enables data exchange while maintaining consistency, eliminating the need for direct translation between incompatible schemas and preventing data corruption.
Solution Approach 2:
The canonical model provides a universal data structure that can serve multiple applications and business units simultaneously. By defining a common schema that multiple applications can adhere to, the system enables broad data exchange capability without the inconsistencies that arise from pairwise translations between different schemas.
2Reliability
If a common schema is enforced across all applications, then data consistency is improved, but legacy applications that do not adhere to the schema cannot communicate
Solution Approach 1:
The canonical model acts as an intermediary layer between legacy applications and the standardized data exchange framework. Legacy applications can communicate with the canonical model using their existing schemas, while the canonical model ensures consistency when data is exchanged with other applications, thus maintaining both data consistency and legacy compatibility.
3Adaptability or versatility
If data translation is performed between different schemas, then communication between applications is enabled, but computation cycles increase and efficiency decreases
Solution Approach 1:
The canonical model is established in advance as a predefined standard schema before data exchange occurs. Applications are configured to adhere to this pre-defined model, eliminating the need for runtime translation and reducing computation cycles. The preliminary establishment of the canonical model enables efficient data exchange without ongoing translation overhead.
4Adaptability or versatility
If multiple schemas are maintained for different applications, then application-specific requirements are met, but data duplication and storage overhead increase
Solution Approach 1:
The patent merges multiple application-specific schemas into a single canonical model that serves as a common data structure. By consolidating schemas into one unified model, the system eliminates redundant data storage while maintaining the ability to meet application-specific requirements through the standardized framework.
Data Source
AI summary
Methods and systems disclosed herein describe a canonical model that sets forth a standardized schema that represents data entities and their relationships as a logical data structure across multiple business units. A schema validator module may validate application-specific schema against the canonical module. Additionally, legacy and/or existing applications may be upgraded, through a transformation module, to comply with the canonical model. The transformation module may transform application-specific data and/or information to the standardized schema, and vice versa, to ensure that legacy and/or existing applications may communicate with applications and/or processing engines that comply with the standardized schema.