Dynamic Data Pipeline Configuration for Fragmented Workflows

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Solution Overview

Problem

Existing data management marketplaces are highly fragmented, requiring businesses to invest significant time and resources in building data processing pipelines that are complex, cumbersome, and prone to errors due to inconsistent tools and processes.

Innovation Solution

A data orchestration system that dynamically configures data processing pipelines by inferring data operations based on user inputs, utilizing machine learning models to recommend and modify data flows, and integrating application performance management for real-time monitoring and resource allocation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If businesses build custom data processing pipelines using fragmented data management marketplaces, then they can access specialized data processing capabilities, but the complexity and time investment increase significantly

Engineering Contradiction:

Improvedata processing capabilityVSAvoidpipeline complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system segments the data processing pipeline into standardized, modular components that can be independently selected and configured. Each component represents a discrete data processing capability that can be combined through configuration files rather than custom coding, reducing overall system complexity while maintaining versatility.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system provides a universal configuration framework that can handle multiple data processing scenarios through a common interface. A single configuration file structure can define pipelines for different data sources, processing logic, and destinations, eliminating the need for separate custom implementations for each scenario.

Inventive Principle:

Principle #6Universality (Multi-functionality)

2Adaptability or versatility

If businesses build custom data processing pipelines from scratch, then they can tailor the pipeline to specific needs, but the time and resource investment increases significantly

Engineering Contradiction:

Improvepipeline customizationVSAvoidpipeline development time

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

The system performs preliminary actions by providing pre-defined, standardized pipeline templates and configuration structures. Users start with pre-configured frameworks that include common data processing patterns, reducing the time needed to build custom pipelines while maintaining the ability to customize specific components.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system enables copying of proven pipeline configurations from templates or existing pipelines. Users can replicate successful pipeline patterns and modify them for specific needs, significantly reducing development time compared to building pipelines from scratch while maintaining customization capability.

Inventive Principle:

Principle #26Copying

3Adaptability or versatility

If fragmented data management tools are used, then specific data processing functions can be achieved, but consistency and reliability decrease

Engineering Contradiction:

Improvedata processing functionVSAvoidpipeline reliability

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The system merges multiple fragmented data management tools into a unified configuration framework. By coordinating diverse data processing components through a single standardized configuration interface, the system ensures consistent behavior and reliable execution across the entire pipeline while maintaining access to various specialized functions.

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The system implements feedback mechanisms that monitor pipeline execution and validate configuration consistency. This ensures that standardized configurations are properly applied across all pipeline components, maintaining reliability while enabling versatile data processing capabilities.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS20250362881A1Dynamically configurable data processing pipeline

Publication Date: 2025.11.27 VIEW SYSTEMS INC

AI summary

This disclosure provides methods, devices, and systems for data management. The present implementations more specifically relate to a data orchestration system that can dynamically or programmatically produce a data processing pipeline. In some aspects, the data orchestration system of the present implementations may infer or otherwise determine the steps to be included in a data processing pipeline with little or no input from a user. In some implementations, the data orchestration system may select the steps based, at least in part, on a set of rules and policies defined by a user. The data orchestration system may further enable the user to modify the recommended data flows in the preconfigured data processing pipeline. In some aspects, the data orchestration system may aggregate data regarding usage, flow, and/or steps across multiple users to detect usage patterns, define repositories, and/or recommend data flows (such as by training a machine learning model).