Software-Defined Data Integration for Unified Multi-Format Assets

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Solution Overview

Problem

Conventional systems integration methods are time-consuming, resource-intensive, and inefficient, particularly in handling diverse data formats and integrating new components, leading to inefficiencies, vendor lock-in, and inconsistent data processing across applications.

Innovation Solution

The implementation of a software-defined systems integration (SDSI) framework that uses data connectors and machine learning models to unify disparate data formats, enabling rapid integration and onboarding of new components, and providing a unified data asset for multiple applications.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If conventional systems integration methods are used to handle diverse data formats and integrate new components, then system functionality is achieved, but integration time and resource consumption increase significantly

Engineering Contradiction:

Improveability to handle diverse data formatsVSAvoidintegration time

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

The patent introduces a software-defined systems integration framework that acts as an intermediary layer between diverse data sources and target systems. This framework includes data connectors and machine learning models that automatically translate and adapt various data formats without requiring custom integration code for each source, thereby reducing integration time while maintaining adaptability to diverse formats

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system dynamically changes parameters such as data format mappings, connection protocols, and processing rules based on the specific data source being integrated. The machine learning models learn and adapt parameters automatically from training data, enabling rapid integration of new data sources without manual configuration, thus resolving the contradiction between handling diverse formats and reducing integration time

Inventive Principle:

Principle #35Parameter changes

2Adaptability or versatility

If conventional systems integration methods are used to integrate new components, then system functionality is achieved, but computational resources and overhead increase significantly

Engineering Contradiction:

Improveability to integrate new componentsVSAvoidcomputational overhead

Core Design Contradiction:

Adaptability or versatilityVSUse of energy by moving object

Solution Approach 1:

The patent implements preliminary action by pre-training machine learning models with training datasets that contain examples of various data formats and integration scenarios. This pre-training enables the models to automatically adapt to new data sources with minimal computational overhead during actual integration, as the heavy lifting of learning patterns has already been performed in advance

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system creates reusable templates and configurations for common data sources and integration patterns. Once a data connector is developed for a particular source type, it can be copied and adapted for similar sources, eliminating the need to develop new integration logic from scratch and reducing computational resources required for integrating new components

Inventive Principle:

Principle #26Copying

3Productivity

If conventional systems integration methods are used, then data integration is achieved, but vendor lock-in and inconsistent data processing occur across applications

Engineering Contradiction:

Improvedata processing consistencyVSAvoidvendor lock-in risk

Core Design Contradiction:

ProductivityVSAdaptability or versatility

Solution Approach 1:

The patent implements a universal data connector framework that can interface with multiple different data sources and target systems through a common architecture. The machine learning models are trained to recognize and process various data formats uniformly, ensuring consistent data processing across different applications and vendors while maintaining the ability to adapt to new sources, thereby eliminating vendor lock-in and ensuring consistency simultaneously

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentEP4607367A1Systems and methods for software defined systems integration

Publication Date: 2025.08.27 PALANTIR TECHNOLOGIES INC

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AI summary

In some examples, systems and methods for systems integration are provided. For example, a method includes: receiving a first data asset in a first data format from a first data source; receiving a second data asset in a second data format from a second data source, the second data format being different from the first data format, the second data source being different from the first data source; performing a correlation process to merge the first data asset in the first data format and the second data asset in the second data format to generate a unified data asset in a common data format, the common data format being different from the first data format, the common data format being different from the second data format; and providing the unified data asset in the common data format to a plurality of software applications.