Semantic Interface for Automated Data Analysis
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Solution Overview
Problem
Existing database analytic tools are inefficient, costly, and require substantial configuration and training, making it difficult for businesses to access and analyze large volumes of data stored in complex data systems.
Innovation Solution
A low-latency data access and analysis system that uses natural language input to automatically transform requests into operable instructions, reducing resource utilization by eliminating the need for manual coding and debugging, and automatically identifying and prioritizing data aggregations, patterns, and anomalies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional database analytic tools are used to access and analyze large volumes of data, then data analysis capability is provided, but resource utilization is high and operation complexity is high
Solution Approach 1:
The system enables self-service data analysis by automatically generating analytical objects and insights without requiring manual coding or configuration. The semantic interface unit autonomously transforms natural language requests into executable queries, and the system automatically identifies patterns, aggregations, and anomalies in the data, eliminating the need for specialized analytical tools and reducing resource consumption.
Solution Approach 2:
The patent replaces complex mechanical systems (traditional database analytic tools requiring manual configuration and coding) with an automated semantic processing system. The semantic interface unit uses natural language processing to substitute manual query construction and data analysis operations with automated text-based interactions, significantly reducing the computational resources required for data analysis.
2Productivity
If traditional database analytic tools are used, then data analysis is performed, but device complexity and operation difficulty increase
Solution Approach 1:
The system provides self-service functionality by automatically generating analytical objects, queries, and insights without requiring user configuration or training. The semantic interface unit autonomously processes natural language requests and transforms them into appropriate database queries, eliminating the complexity of traditional analytic tool configuration while maintaining robust data analysis capabilities.
Solution Approach 2:
The semantic interface unit serves multiple functions: it processes natural language input, generates analytical objects, constructs database queries, and presents results in natural language. This multi-functional approach consolidates what would traditionally require multiple separate tools and configuration steps into a single universal interface, reducing device complexity while maintaining comprehensive data analysis capability.
3Measurement precision
If manual coding and debugging are used for data requests, then precise data access is achieved, but time consumption and resource utilization increase
Solution Approach 1:
The system performs self-service by automatically transforming natural language data requests into precise executable queries without requiring manual coding or debugging. The semantic interface unit autonomously interprets the intent of natural language requests, generates appropriate analytical objects, and constructs accurate database queries, maintaining data access precision while eliminating time-consuming manual programming activities.
Solution Approach 2:
The system performs preliminary actions by pre-processing natural language requests through semantic analysis and automatically generating the appropriate query structure before execution. The semantic interface unit prepares analytical objects and query plans in advance, eliminating the need for iterative coding and debugging while ensuring precise data access through pre-validated query construction.
4Quantity of substance
If complex data structures are used to maximize data density, then storage efficiency is improved, but data accessibility and ease of operation deteriorate
Solution Approach 1:
The semantic interface unit acts as an intermediary between the user and the complex data structures. It translates natural language requests into appropriate queries that navigate the complex normalized database schema without requiring users to understand the underlying data structure complexity. This intermediary layer maintains ease of operation while preserving the storage efficiency benefits of complex data structures.
Solution Approach 2:
The system provides self-service data access by automatically handling the complexity of navigating normalized database structures. The semantic interface unit autonomously generates analytical objects and constructs queries that efficiently access data across multiple normalized tables, eliminating the need for users to manually manage or understand complex data structures while maintaining optimal storage density.
Data Source
AI summary
Generating object morphisms during object search includes obtaining object-search request data, wherein the object-search request data includes object-search terms, obtaining resolved-request data representing the object-search terms, determining that a first analytical object partially consistent with the resolved-request data is available, wherein the first analytical object is consistent with a first portion of the resolved-request data, generating candidate object-morphism data with respect to the first analytical object in accordance with a second portion of the resolved-request data, outputting object-search response data including the candidate object-morphism data for presentation to a user, obtaining data indicating a selected object morphism from the candidate object-morphism data, generating a second analytical object in accordance with the first analytical object and the selected object morphism, wherein the second analytical object differs from the first analytical object, and outputting response data including the second analytical object for presentation to the user.