Universal Vendor Data Adapter for Standardized Pipelines
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Solution Overview
Problem
Large organizations face inefficiencies in managing and 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, facilitated by a controller that selects and configures data adapters, and a data streaming processor to create pipelines for data transformation and distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple separate applications are used to handle vendor data from different vendors, then each business unit can access its specific vendor data, but the system complexity increases and data standardization becomes difficult
Solution Approach 1:
The patent implements a universal adapter framework that can handle multiple vendor data formats through a single standardized interface. The adapter layer provides multi-functionality by supporting various vendor-specific protocols and data structures while presenting a uniform organizational data model to all business units, eliminating the need for separate applications for each vendor.
Solution Approach 2:
The adapter framework acts as an intermediary layer between vendor data sources and organizational systems. This mediator translates and standardizes vendor-specific data formats into a common organizational data model, simplifying the system architecture by centralizing data conversion logic rather than requiring multiple separate applications.
2Ease of operation
If vendor data is stored in various formats across different computing devices, then each device can process data in its native format, but data accessibility and operational efficiency decrease
Solution Approach 1:
The patent transforms vendor data by changing its format parameters from diverse vendor-specific structures to a standardized organizational data model. This parameter transformation enables consistent data access across all systems while reducing redundant storage requirements, as standardized data can be efficiently cached and shared across multiple business units.
3Stability of the object's composition
If a centralized system standardizes all vendor data formats, then data consistency improves, but the complexity of data conversion and processing increases
Solution Approach 1:
The patent segments the data conversion process into modular adapter components, each handling specific vendor formats. This segmentation reduces conversion complexity by breaking down the overall transformation task into manageable, reusable modules that can be independently configured and maintained, while still achieving centralized data consistency.
Solution Approach 2:
The adapter framework performs preliminary data standardization at the point of ingestion, converting vendor data to the organizational data model before it enters the main system. This preliminary action eliminates the need for complex real-time conversion operations downstream, reducing processing complexity while maintaining data consistency.
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.