Universal Vendor Data Adapter for ML-Driven Pipeline Standardization
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Solution Overview
Problem
Large organizations face inefficiencies in leveraging vendor data due to diverse data formats from various vendors, leading to challenges in converting and standardizing this data for organizational use across different business units.
Innovation Solution
A universal data adapter system utilizing machine learning to transform vendor-specific data into a consistent organizational format, managed by a controller that selects and configures data adapters, and employs data streaming processors to create pipelines for data transformation and distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If vendor-specific data formats are used directly, then data storage space is reduced, but data accessibility and standardization across the organization deteriorate
Solution Approach 1:
The patent introduces a data adapter as an intermediary component that sits between vendor-specific data sources and the organizational data system. This adapter translates and standardizes vendor data into a universal format without requiring changes to the original vendor systems or complete restructuring of organizational data storage. The adapter serves as a mediator that enables data accessibility and standardization while preserving the original vendor data formats for storage efficiency.
2Productivity
If multiple applications operate on various computing devices to handle vendor data, then data processing capability is improved, but system complexity increases
Solution Approach 1:
The patent implements a universal data adapter that can handle multiple vendor data formats and protocols through a single standardized interface. This multi-functional adapter eliminates the need for separate applications on various computing devices to handle different vendor formats, thereby reducing system complexity while maintaining data processing capability. The adapter provides a unified entry point for all vendor data regardless of source.
3Productivity
If vendor data is standardized across the organization, then data utilization efficiency is improved, but data transformation complexity increases
Solution Approach 1:
The patent implements preliminary action by having the data adapter automatically perform data transformation and standardization at the point of data ingestion, before the data enters the organizational system. This preliminary standardization eliminates the need for complex manual transformation processes later in the data workflow. The adapter pre-processes vendor data into standardized formats, thereby improving data utilization efficiency without requiring complex transformation operations downstream.
Data Source
AI summary
An electronic online system is configured to receive, at the electronic online system, an expression of a use case; determine, using a first machine-learning technique with the expression of the use case as input, a data source to satisfy the use case; determine, using a second machine-learning technique with the expression of the use case and the inference of the first machine-learning technique as inputs, a data destination to satisfy the use case; and construct a data pipeline from the data source to the data destination for the use case.