Dynamic Data Model for Synchronizing Disparate Applications

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Solution Overview

Problem

Existing computing systems lack modularity and flexibility, unable to dynamically integrate with a scalable structure that can handle various data types and formats without additional data structures and high load processing routines.

Innovation Solution

The system processes and transforms data from multiple sources and formats, using application programming interfaces (APIs) and data transformation processes to create a dynamic data analytics system that synchronizes data across multiple applications, with customizable access levels.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If existing computing systems use fixed data structures and processing routines to handle data integration, then data processing can be performed with established methods, but the system lacks modularity and flexibility to dynamically integrate with various data types and formats

Engineering Contradiction:

Improveflexibility to handle various data types and formatsVSAvoidsystem structure complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system divides data processing into independent modules: data collection module, data validation module, data transformation module, and data synchronization module. Each module handles specific tasks independently, allowing the system to process various data types and formats without requiring complete system redesign, thus achieving flexibility while managing complexity through modular architecture

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system introduces an intermediary data transformation layer that acts as a mediator between diverse data sources and the core processing system. This transformation layer converts various data formats into a standardized internal representation, enabling the system to handle multiple data types without increasing core processing complexity

Inventive Principle:

Principle #24Intermediary (Mediator)

2Adaptability or versatility

If the system processes data from multiple sources with varying formats, then data synchronization capability is improved, but processing load and system performance deteriorate

Engineering Contradiction:

Improvedata synchronization capabilityVSAvoidprocessing load and system performance

Core Design Contradiction:

Adaptability or versatilityVSProductivity

Solution Approach 1:

The system performs preliminary data validation and transformation actions before data enters the core processing queue. By validating data formats and transforming data structures in advance, the system reduces the processing burden on subsequent operations, maintaining high throughput while handling diverse data sources

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements continuous data processing with overlapping operations: while one module validates data, another transforms it, and a third synchronizes it. This pipelined approach ensures continuous productive action without idle waiting time, maintaining high processing efficiency despite the complexity of handling multiple data formats

Inventive Principle:

Principle #20Continuity of useful action

3Reliability

If the system implements comprehensive data validation and transformation processes, then data quality and synchronization accuracy are improved, but processing time and system response time increase

Engineering Contradiction:

Improvedata quality and synchronization accuracyVSAvoidprocessing time and system response time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system applies data validation and transformation rules selectively based on the specific data type and source rather than uniformly to all data. By tailoring validation depth and transformation complexity to local data characteristics, the system maintains high accuracy for critical data while reducing processing time for less critical data types

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The system implements feedback mechanisms that monitor data processing quality and performance in real-time. When validation errors or performance bottlenecks are detected, the system dynamically adjusts validation strictness and transformation parameters, balancing data quality requirements with processing speed without requiring manual intervention

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS12216784B1Systems and processes for synchronizing disparate applications

Publication Date: 2025.02.04 MEDTRANS GO INC

AI summary

Systems and processes for synchronizing disparate applications are described herein. In various embodiments, the process includes: (1) receiving and validating a log-in request; (2) receiving a request submission comprising a plurality of data items; (3) writing the plurality of data items into a dynamic and scalable data model; (4) determining request parameters associated with the plurality of data items; (5) determining a recommended deployment strategy based on the one or more parameters and characteristic values stored in the data model; (6) generating a and transmitting one or more notifications according to the recommended deployment strategy; and (7) generating and/or modifying a display based on the notification(s).