Parameterized Data Source Integration for Analytics Systems
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Solution Overview
Problem
Existing systems face challenges in seamlessly integrating various application systems with analytics systems for user querying, due to unique data structures and the need for data replication, which complicates data management and retrieval.
Innovation Solution
A method that involves obtaining an analytical data model with base data sources and structural definitions, identifying parameters, generating modified data sources by injecting parameters into base data sources, and executing user queries based on these modified sources to provide results, thereby facilitating flexible integration and data retrieval without replication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If data replication is used to integrate application systems with analytics systems, then data access capability is improved, but system complexity and data management overhead increase
Solution Approach 1:
The patent introduces an intermediary layer (analytics gateway or integration layer) that sits between application systems and analytics systems. This intermediary translates data requests from the analytics system into application system-specific queries, eliminating the need for data replication while maintaining fast access capability. The intermediary handles protocol translation and data format conversion, reducing system complexity.
Solution Approach 2:
Instead of replicating actual data, the patent creates virtual copies or views of data through parameterized data source definitions. These virtual copies allow the analytics system to query data without physical replication, maintaining data access speed while reducing storage complexity and synchronization overhead.
2Measurement precision
If unique data structure handling is implemented for each application system, then data retrieval accuracy is improved, but integration complexity increases
Solution Approach 1:
The patent creates a universal integration framework that can handle multiple application system data structures through a common interface. The system uses parameterized data source definitions and adaptive query generation to work with different data structures without requiring separate handling logic for each system, thus maintaining retrieval accuracy while reducing integration complexity.
Solution Approach 2:
The patent employs parameterized data source definitions where data structure characteristics are defined through parameters rather than hard-coded logic. This allows the system to adapt to different application system structures by changing parameters dynamically, maintaining precision while simplifying the integration framework through configuration rather than complex programming.
3Device complexity
If data replication is avoided for seamless integration, then system simplicity is improved, but data access flexibility deteriorates
Solution Approach 1:
The patent implements dynamic query generation that adapts to different data sources in real-time without requiring data replication. The system dynamically modifies queries based on the target data source's structure and capabilities, providing data access flexibility while maintaining system simplicity through a single unified integration approach rather than multiple replicated data copies.
Data Source
AI summary
A data source integration architecture is provided for integrating application systems with an analytics system for user querying and data retrieval. The integration includes flexibly configuring base data sources as defined by an analytical model of an application system, such as an OEM application. In response to a query, metadata is fetched from an application server, where the metadata may contain a description of underlying artifacts of the structural part of the analytical model. During query generation, these specific views are injected into a query view and a parametrization is added for data source modulation. In addition, a flexible configuration of the final shape of the base data source specifically allows for the requirements of the OEM application to be addressed.