Natural Language Query Interface for KPI Analytics
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Solution Overview
Problem
Users tasked with analyzing key performance indicators (KPIs) in cloud-based systems often require complex database query languages, which can be a barrier due to lack of expertise and leads to substantial costs and delays in accessing and visualizing KPI data.
Innovation Solution
An analytics server that enables natural language queries (NLQs) for accessing and analyzing KPI data, featuring a graphical user interface (GUI) that suggests queries based on user access and previous queries, and uses a natural language processor to generate database queries for visual representation without requiring knowledge of complex query languages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex database query languages are used to access and analyze KPI data, then measurement precision and data analysis capability are improved, but ease of operation deteriorates due to lack of user expertise
Solution Approach 1:
The patent introduces a natural language processing intermediary layer between the user and the complex database query system. Users can submit queries in natural language through a chat interface, and the system automatically translates these into appropriate database queries using NLP and LLM technologies. This intermediary eliminates the need for users to learn complex query languages while maintaining full access to KPI data analysis capabilities.
2Manufacturing precision
If specialized expertise in database query languages is required, then manufacturing precision of data retrieval is improved, but productivity deteriorates due to training requirements and delays
Solution Approach 1:
The system implements self-service capabilities where the AI assistant automatically understands user intent, formulates appropriate database queries, retrieves KPI data, and presents results without requiring user expertise. The system includes features like automatic query optimization, result interpretation, and even suggests relevant KPIs based on user needs, enabling non-experts to perform complex data analysis tasks immediately without training delays.
3Adaptability or versatility
If comprehensive KPI data access is enabled, then adaptability of the system is improved, but device complexity increases due to additional processing layers
Solution Approach 1:
The patent implements a universal AI assistant that handles multiple functions within a single interface: natural language understanding, query formulation, data retrieval, result visualization, and even suggesting relevant KPIs. The system uses a multi-functional architecture where the LLM and NLP components serve multiple purposes including intent recognition, query optimization, and result interpretation, reducing the need for separate specialized systems while maintaining high adaptability.
Data Source
AI summary
An analytics server is disclosed that enables natural language queries (NLQs) to be used to access key performance indicator (KPI) data. The analytics server includes a graphical user interface (GUI) that presents a set of KPIs associated with a user. The GUI includes suitable user interface elements to enable the user to provide natural language queries regarding these KPIs. The user interface elements provide the user with suggested NLQs based on, for example, KPIs to which the user has access and/or previous NLQs of the user. In response to the analytics server receiving a suitable NLQ from the user, the analytics server generates an appropriate database query to retrieve the KPI data requested by the NLQ. The GUI is then updated to present a visual representation (e.g., a bar graph, a pie chart, a trend line, a single value) of the retrieved KPI data.