Business Intelligence Search System for Natural Language Query Translation
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Solution Overview
Problem
Business intelligence systems lack user-friendly interfaces that allow non-sophisticated users to perform textual searches on complex databases and data warehouses, failing to provide accessible and understandable responses, especially on mobile devices.
Innovation Solution
A business intelligence search system that translates textual queries into query languages like SQL, generates visualizations, and learns user preferences through interaction data to provide intuitive access to data stored in databases and data warehouses, using a client-server architecture with components like search query rewriters, index searchers, and text-to-query generators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If complex query structures and reports in database vernacular are used to access information, then the system can retrieve accurate data from databases and data warehouses, but typical users cannot access this information due to lack of sophistication and training
Solution Approach 1:
The patent introduces a natural language processing intermediary layer between users and database query structures. Users input questions in plain English through a chat interface, and the system automatically translates these into appropriate SQL queries and visualizations, eliminating the need for users to learn complex query languages while maintaining accurate data retrieval
Solution Approach 2:
The patent replaces the mechanical system of learning and using complex query syntax with an automated natural language processing system. Instead of users manually constructing queries according to database vernacular rules, the system uses AI to interpret user intent and generate appropriate queries automatically
2Adaptability or versatility
If traditional business intelligence systems are designed for sophisticated users with training, then they can effectively query complex data stores, but they fail to provide accessible interfaces for typical users who want simple textual searching
Solution Approach 1:
The patent makes the business intelligence system universal by implementing a multi-functional interface that serves both sophisticated users and typical users. The same chat interface can handle simple natural language queries from novice users and complex analytical requests from experienced users, automatically adjusting the level of abstraction and explanation provided
Solution Approach 2:
The patent implements dynamic adaptation where the system adjusts its response format, level of detail, and explanation based on user interaction patterns and preferences. The interface dynamically modifies itself to match user expertise levels while maintaining access to complex data warehouse capabilities
3Loss of information
If business intelligence systems provide detailed query results in traditional formats, then they contain complete information, but they do not produce responses in formats that users can easily understand
Solution Approach 1:
The patent transforms query results from traditional tabular formats into visual dimensions such as charts, graphs, and interactive visualizations. This dimensional transformation maintains all the underlying data information while presenting it in visually intuitive formats that are easier for users to understand and interpret
Solution Approach 2:
The patent introduces a natural language explanation intermediary that translates complex query results into plain English summaries. The system provides both the complete detailed data for accuracy and automated narrative explanations for understandability, bridging the gap between information completeness and user comprehension
4Adaptability or versatility
If users need to access data wherever they are located using mobile devices, then users gain flexibility and mobility, but traditional business intelligence systems do not support mobile access with textual query input
Solution Approach 1:
The patent implements a universal chat interface that functions consistently across desktop and mobile devices. The same natural language processing capabilities and visualized response formats are available on mobile devices, enabling users to perform complex data warehouse queries using simple text input anywhere they have internet connectivity
Data Source
AI summary
A computer-implemented method of executing a user query includes presenting a user interface to allow a user to enter a query, receiving a user-entered textual request through the interface, launching a search service to rewrite the textual request into a search query, sending the search query to a presentation server, receiving an answer to the query, and returning the answer to the user as a graphical representation. A computer-implemented method includes receiving a crawl request from a user, launching a crawl manager to monitor the crawl request and track statistics related to the crawl, starting a crawl task based upon the crawl request, indexing a business intelligence presentation server to create a data index, and storing the data index.