Generic SQL Plugin for Unified Console Data Integration
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Solution Overview
Problem
Current systems require significant time and effort to integrate SQL data servers into consoles, necessitating the development of plugin components that can take weeks, and existing business intelligence tools do not automatically build logical layers from database tables for unified data access.
Innovation Solution
A unified OSS console platform with a generic SQL plugin that automatically generates and customizes value pack definitions for SQL database tables, allowing for rapid integration and unified data access across heterogeneous data sources, using a JSON-based logical model and plugin components for data access and visualization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual plugin components are developed for SQL data server integration, then data access capability is achieved, but integration time and effort increase significantly
Solution Approach 1:
The system performs self-configuration by automatically generating value pack definitions from SQL database schemas. The SQL plugin executes queries against the database, retrieves table and column metadata, and autonomously creates the corresponding value pack structures without requiring manual configuration files or extensive developer intervention.
Solution Approach 2:
The system performs preliminary actions by pre-generating value pack definitions during the integration process. Instead of requiring manual setup after deployment, the plugin proactively creates the logical layer structure, data models, and access configurations before the system is fully operational, reducing subsequent setup time.
2Adaptability or versatility
If custom plugin components are developed for each data source, then data access is enabled, but system complexity increases
Solution Approach 1:
The SQL plugin implements a universal interface that handles multiple SQL database types (MySQL, PostgreSQL, SQL Server, etc.) through a single component. The plugin uses standardized value pack definitions and configuration formats that work across different database systems, eliminating the need for separate custom plugins for each data source type.
Solution Approach 2:
The system enforces homogeneous data access patterns by requiring all SQL databases to be accessed through the same value pack definition structure. The plugin normalizes different database schemas into a unified logical model format, allowing consistent access methods and reducing the complexity of handling diverse data source formats.
3Loss of time
If automatic value pack generation is implemented, then integration time is reduced, but automation extent increases
Solution Approach 1:
The system incorporates feedback mechanisms where the generated value pack definitions are validated against the actual database schema. The plugin executes test queries to verify that the automatically created data models accurately represent the source database structure, and allows for iterative refinement based on validation results.
Solution Approach 2:
The value pack definition serves as an intermediary layer between the SQL database and the application logic. This intermediate representation decouples the database-specific details from the application code, allowing automatic generation while maintaining system flexibility and ease of modification.
Data Source
AI summary
Systems and methods of automating the generation of a logical model defining one or more tables of a data source are provided. The logical model definitions of the tables can be exposed to a platform that can access and obtain data from multiple heterogeneous data sources based on a unified and normalized format. Tables of a data source can be analyzed to determine key characteristics, and based on the key characteristics, converted into dimension and fact table representations, objects, and operations that comport with the unified and normalized format. Default rules for generating the dimension and fact table representations, objects, and operations can be followed, or user-defined customizations can be implemented.