Visual Data Pipeline Mapping for External Model Integration
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Solution Overview
Problem
Configuring industrial data pipelines is a complex task requiring expertise, and integrating external analytic models into enterprise-specific data pipelines can be challenging due to lack of knowledge about the end user's data schema and naming conventions.
Innovation Solution
A data pipeline configuration system that allows intuitive visual configuration using a graphical interface to select and arrange pipeline components, including data sources, processing components, and analytic models, with adapters to map incoming data and publish results to specified destinations, enabling easy integration of external models without requiring extensive data engineering expertise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a visual configuration interface is provided for data pipeline setup, then ease of operation is improved, but device complexity increases due to the need for graphical interface components and configuration processing logic
Solution Approach 1:
A visual configuration interface acts as an intermediary between the user and the complex data pipeline system. The interface provides graphical elements representing data sources, analytic models, and destinations, allowing users to configure pipelines through visual selection and arrangement rather than direct programming. This mediator translates user-friendly visual actions into the underlying system configuration, resolving the contradiction by shielding users from complexity while maintaining system functionality.
2Adaptability or versatility
If adapters are provided to map incoming data and publish results, then adaptability is improved, but device complexity increases due to additional mapping and integration components
Solution Approach 1:
The system implements universal adapter components that can handle multiple data sources, analytic models, and destinations through standardized interfaces. These adapters provide multi-functional capabilities to map incoming data from various schemas and publish results to different destinations without requiring separate custom components for each scenario. This universality increases adaptability while controlling complexity by reusing the same adapter framework across different integration scenarios.
Data Source
AI summary
A data pipeline configuration system allows industrial data pipelines to be configured using an intuitive visual interface. The pipeline configuration system allows graphical pipeline components representing data sources, data processing, analytic or machine learning models, and emitters to be selectively added to an industrial data pipeline application by selecting these components from a library. The pipeline configuration application is created by arranging and linking these selected pipeline components within a pipeline builder section of the configuration system's visual design interface. The design interface also allows analytic or machine learning models to be easily integrated into the pipeline application and mapped to incoming data items, such that the model is applied and scored against incoming data during pipeline operation. The configuration system also allows the user to configure destinations or data sinks for the pipeline data, including both the incoming industrial data and model scoring results.