Automated Data Stream Dashboard Generation via Domain Model Analysis

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Solution Overview

Problem

Existing methods for generating data stream dashboards require manual configuration of data source entities, often ignoring relationships between data source entities, leading to redundant logic and high data collection overhead, resulting in poor quality dashboards.

Innovation Solution

A method that involves acquiring a domain model diagram of a service system and multiple data sources, determining relationship data among domain entities based on a representation vector, and using this data to generate a dashboard for visualizing data streams by determining data source entity relationships, data stream relationships, and impact factors.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If manual configuration of data source entities is used, then the dashboard can be customized based on product or service requirements, but the process causes poor quality of the finally generated data stream dashboard due to ignored relationships and redundant logic

Engineering Contradiction:

Improvedashboard customizationVSAvoiddashboard quality

Core Design Contradiction:

Adaptability or versatilityVSManufacturing precision

Solution Approach 1:

The system performs preliminary analysis of data source entity relationships before dashboard generation. By pre-processing the domain model diagram and establishing entity relationships in advance, the system avoids the need for manual configuration while ensuring high dashboard quality through automated relationship detection and data stream analysis.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system enables self-service dashboard generation by automatically analyzing data source entities and their relationships without requiring manual developer intervention. The automated system extracts entity relationships from domain model diagrams and generates dashboards based on detected data stream relationships, eliminating manual configuration errors and improving dashboard quality.

Inventive Principle:

Principle #25Self-service

2Ease of operation

If manual configuration of data source entities is used, then the dashboard can be created based on developer experience, but this leads to high data collection overhead and redundant logic

Engineering Contradiction:

Improvedashboard creationVSAvoiddata collection overhead

Core Design Contradiction:

Ease of operationVSLoss of time

Solution Approach 1:

The system replaces the mechanical manual configuration process with an automated computational system. Instead of developers manually specifying data source entities based on experience, the system automatically analyzes domain model diagrams and detects entity relationships through computational methods, eliminating manual labor and reducing data collection overhead.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system introduces an intermediary automated analysis layer between the domain model diagram and the dashboard generation process. This intermediary automatically extracts entity relationships and identifies data stream relationships, serving as a mediator that eliminates the need for manual configuration while maintaining ease of operation through automated processing.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Adaptability or versatility

If manual configuration of data source entities is used, then the dashboard can be specified based on service requirements, but relationships of the data source entity are often ignored

Engineering Contradiction:

Improveservice requirement specificationVSAvoiddata source entity relationships

Core Design Contradiction:

Adaptability or versatilityVSLoss of information

Solution Approach 1:

The system performs preliminary extraction and analysis of data source entity relationships from domain model diagrams before dashboard generation. By pre-processing the domain model and establishing entity relationships in advance, the system ensures that no relationship information is lost during the dashboard creation process, while still maintaining adaptability to service requirements.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements feedback mechanisms that automatically detect and validate data source entity relationships during the dashboard generation process. By continuously analyzing the domain model diagram and comparing detected relationships with service requirements, the system ensures that no relationship information is lost while maintaining adaptability to specific service needs.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS20250028545A1Method for generating dashboard for visualizing data streams and apparatus, computer device, and storage medium

Publication Date: 2025.01.23 TENCENT TECHNOLOGY (SHENZHEN) CO LTD

AI summary

A method for generating a dashboard for visualizing data streams is applicable to the fields of cloud computing and intelligent transportation. The method includes acquiring a domain model diagram of a service system and at least two data sources; determining relationship data among all domain entities in the domain model diagram based on a first representation vector of the domain model diagram; determining a data source entity relationship, a data stream relationship, and impact factors of the at least two data sources based on the relationship data and the at least two data sources; and generating a dashboard for visualizing data streams of the service system based on the data source entity relationship, the data stream relationship, and the impact factors.