Real-Time Enterprise Data Integration Service
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Solution Overview
Problem
Current enterprise application integration methods operate in batch mode, leading to inefficiencies such as repetitive data handling and delayed access to data across different applications, failing to provide real-time data integration.
Innovation Solution
The development of methods and systems for real-time data integration that process requests from multiple data sources, integrate data in real-time, and expose the results as a service, allowing access through a graphical user interface without additional coding, supporting both real-time and batch modes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If batch mode data integration is used, then data integration can be performed across multiple applications, but data availability is delayed and not real-time
Solution Approach 1:
The system transitions from static batch processing to dynamic real-time processing. The data integration service continuously processes data requests as they arrive, adapting to changing data needs in real-time rather than following a fixed batch schedule. This allows the system to maintain data consistency while providing immediate data availability when needed.
Solution Approach 2:
The patent implements continuous data integration processing where the service remains active and processes data requests continuously rather than in periodic batches. This continuous operation ensures that data is integrated and made available in real-time while maintaining consistency across applications, eliminating the waiting period inherent in batch processing.
2Productivity
If specialized computer applications are used for different business processes, then each process can be optimized, but data integration becomes complex and requires repetitive handling
Solution Approach 1:
The patent creates a universal data integration service that can handle multiple data sources and target applications through a single interface. This service performs extraction, transformation, and loading operations for various business processes without requiring separate integration systems for each application, thereby maintaining process efficiency while reducing overall integration complexity.
Solution Approach 2:
The data integration service acts as an intermediary layer between specialized business applications and underlying data sources. This mediator handles all data integration operations centrally, eliminating the need for each application to have its own integration logic and reducing repetitive data handling across the enterprise.
3Quantity of substance
If batch mode data extraction and loading is used, then large amounts of data can be processed, but the process takes time and is not available in real-time
Solution Approach 1:
The system implements periodic data processing where large volumes of data are extracted and loaded in structured intervals or triggers rather than continuous streams. This allows the system to handle substantial data quantities while reducing overall processing time by organizing operations efficiently, providing real-time availability without sacrificing processing capacity.
Data Source
AI summary
Methods and systems for enterprise data integration are described. The methods and systems take elements of a data integration process typically operating in a batch-mode, transform the elements in real time, and expose the results as a service that can be accessed by a business enterprise in real time, and optionally also in batch mode. The service can be accessed through a graphical user interface, providing automatic data integration in real time without additional coding. The service can also operate with mobile devices.