Table Graph for Multi-Source Database Querying
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional database querying methods are inefficient as they require skilled programmers to format queries specifically for each data source, consume significant processing and memory resources, and involve lengthy software development cycles, even for minor changes, and struggle with handling multiple data sources simultaneously.
Innovation Solution
A system utilizing a 'table graph' that represents data sources and their relationships, allowing unskilled users to interactively query multiple data sources through a graphical interface, automatically formulating queries and providing results without the need for complex programming knowledge, and enabling parallel querying to reduce processing and memory usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional database querying methods are used, then queries can be executed on data sources, but skilled programmers are required to format queries specifically for each data source, increasing operation difficulty
Solution Approach 1:
The patent introduces an intermediary layer (the system with graphical interface) that translates user-friendly search criteria into database-specific queries. This intermediary handles the complexity of different data source formats, allowing users to query multiple data sources without needing to know the specific formatting requirements of each source.
Solution Approach 2:
The system provides a universal querying interface that can handle multiple different data sources through a single unified method. The graphical user interface and automated query formulation capabilities enable the same interface to work across various database types and formats, eliminating the need for separate querying tools for each data source.
2Productivity
If traditional database querying methods are used, then data can be accessed, but significant processing and memory resources are consumed
Solution Approach 1:
The system performs preliminary actions by pre-defining the query structure and data relationships in a graphical format before execution. The automated query formulation and parallel processing capabilities prepare the querying approach in advance, optimizing resource usage before actual data retrieval occurs.
Solution Approach 2:
The patent segments the querying process into independent parallel operations. Multiple data sources can be queried simultaneously through parallel processing, dividing the overall task into smaller concurrent operations that reduce total processing time and improve resource utilization efficiency.
3Productivity
If traditional software development tools are used for generating queries, then queries can be created and tested, but an entire software development life cycle is required even for minor changes, increasing time consumption
Solution Approach 1:
The system provides dynamic query modification capabilities through the graphical interface. Users can easily modify search criteria and query parameters without going through formal development cycles. The system dynamically adapts to user inputs and makes real-time adjustments to queries, enabling rapid iteration and updates.
Solution Approach 2:
The system performs self-service by automatically formulating and optimizing queries based on user inputs. The automated query generation and execution capabilities eliminate the need for manual programming and testing cycles, allowing users to quickly modify and execute queries without requiring software development processes.
4Adaptability or versatility
If traditional querying methods are used, then data sources can be accessed, but difficulties arise when handling queries to various types of data sources at the same time
Solution Approach 1:
The system provides a universal interface that can handle multiple different data sources through a single unified method. The graphical user interface and automated query formulation capabilities enable the same interface to work across various database types and formats, eliminating the need for separate querying tools for each data source.
Solution Approach 2:
The patent introduces an intermediary layer that translates user-friendly search criteria into database-specific queries for multiple data sources. This intermediary handles the complexity of different data source formats and enables parallel processing, allowing seamless access to heterogeneous data sources without increasing user burden.
Data Source
AI summary
Embodiments of the present disclosure relate to a computer system and interactive user interfaces configured to enable efficient and rapid access to multiple different data sources simultaneously, and by an unskilled user. The unskilled user may provide simple and intuitive search terms to the system, and the system may thereby automatically query multiple related data sources of different types and present results to the user. Data sources in the system may be efficiently interrelated with one another by way of a mathematical graph in which nodes represent data sources and/or portions of data sources (for example, database tables), and edges represent relationships among the data sources and/or portions of data sources. For example, edges may indicate relationships between particular rows and/or columns of various tables. The table graph enables a compact and memory efficient storage of relationships among various disparate data sources.