Natural Language Data Support for Faster Insight Resolution
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Solution Overview
Problem
Existing data platforms face challenges in providing efficient and scalable support for users seeking insights, leading to increased ticket resolution times and potential loss of critical insights due to manual handling by multi-tiered support teams.
Innovation Solution
A system utilizing a natural language model to automatically generate enhanced descriptions based on user requests, incorporating machine learning algorithms and heuristics for context classification and relevancy analysis, supported by a chatbot and data assistant tool for self-serve capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual support handling is used, then user support can be provided, but ticket resolution time increases and scalability is limited
Solution Approach 1:
The system enables self-service support by allowing users to query data platform insights directly through natural language interfaces. The automated assistant retrieves and processes information from data sources without requiring manual intervention from support teams, enabling users to resolve their own queries independently.
Solution Approach 2:
The patent replaces manual mechanical processing of support tickets with an automated computational system. The system uses processors to retrieve data from sources, natural language models to understand and generate responses, and automated workflows to handle ticket processing, substituting human manual operations with digital automation.
2Reliability
If multi-tiered manual support team is used, then comprehensive support can be provided, but system complexity and operational burden increase
Solution Approach 1:
The system extracts the support function from the complex multi-tiered human organization and implements it as an independent automated system. By taking out the support capability and implementing it through automated data retrieval, natural language processing, and computational workflows, the system eliminates the need for complex hierarchical support structures while maintaining comprehensive support coverage.
3Productivity
If automated system is implemented, then scalability is improved, but system complexity increases
Solution Approach 1:
The automated system is designed with multi-functionality to handle diverse support queries across different domains. The natural language model and data retrieval mechanisms can adapt to various types of questions about data platforms, enabling a single unified system to serve multiple functions and query types without requiring separate specialized systems for each domain.
Data Source
AI summary
Systems and methods for automatically providing data and insight supports using a natural language model are disclosed. In some embodiments, a disclosed method includes: receiving, from a computing device, a support request seeking an insight about a data platform; retrieving, based on the support request, an original description from at least one data source associated with the data platform; computing, using a natural language model, a degree of relevancy of the original description regarding the support request; generating, according to the degree of relevancy, a context description based on the original description; generating, using the natural language model, an enhanced description based on the context description; and transmitting the enhanced description to the computing device.