Non-structured Data Database Communication System
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Solution Overview
Problem
Current systems for managing and communicating with third-party databases in enterprise environments require extensive knowledge of query languages, making it complex and costly for businesses to access and manage data, especially for survey data collection and analysis.
Innovation Solution
A system utilizing non-structured-data-oriented language code and an application programming interface (API) allows users to communicate with third-party management databases through search-style queries, enabling users to access and manage data without comprehensive knowledge of database relationships, with features like auto-completion and real-time data access for survey management and workflow monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional query languages are used to communicate with third-party databases, then data access capability is achieved, but system complexity and cost increase due to requiring extensive user knowledge
Solution Approach 1:
The patent introduces an intermediary layer (the system described in the patent) that translates between simple natural language queries and complex database query languages. This intermediary handles the complexity of database communication internally while presenting a simplified interface to users, thereby improving ease of operation without sacrificing data access capability.
2Measurement precision
If extensive knowledge of query language is required, then precise data retrieval is achieved, but user accessibility and adoption decrease
Solution Approach 1:
The system provides self-service functionality by automatically understanding and processing natural language queries without requiring users to learn complex query languages. The system handles translation, optimization, and execution internally, making precise data retrieval accessible to users with varying levels of technical expertise.
Solution Approach 2:
The patent changes the parameter of query language complexity from high to low by translating natural language (simple parameter) into database query language (complex parameter) internally. This allows the system to maintain precise data retrieval capabilities while presenting a user-friendly interface with simplified parameters.
3Reliability
If specialized query language expertise is mandated, then accurate data management is achieved, but operational cost and time investment increase
Solution Approach 1:
The system performs preliminary action by pre-compiling and optimizing translation rules between natural language and database query languages. It prepares the translation framework in advance, so when users submit queries, the system can quickly translate and execute them without requiring users to invest time in learning complex query languages or syntax.
Data Source
AI summary
Techniques for communicating with a third-party management database are described herein. According to an embodiment, a computer receives a search-style query, searches the third-party management database, retrieves multiple computer-readable database search strings, displays the computer-readable database search strings, and receives a selected computer-readable database search string. In response, the computer queries the third-party management database using the selected search string, returns a temporary variable associated with a supplier risk score, and receives a command to perform a decision step as part of a workflow.