Natural Language Insight Engine for Automated Data Analysis
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Solution Overview
Problem
Business organizations face challenges in extracting valuable insights from large volumes of data due to the reliance on manual interpretation using business intelligence tools, which are limited to displaying data in tables and graphs, and often require specialized skills in statistics, data mining, and programming, leading to person-dependent and tool-dependent insights, and the scarcity of data scientists.
Innovation Solution
A system and method for generating natural language insights that define analysis processes for questions, identify dimensions and measures, and use attribute-weighted data mining algorithms to collect and analyze data, providing natural language answers through various formats like emails or web pages, mimicking the insights a qualified data scientist would derive.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual interpretation using business intelligence tools is used, then data can be displayed in tables and graphs, but the insight gained is person-dependent and tool-dependent, and requires specialized skills
Solution Approach 1:
The patent introduces an automated analysis system that acts as an intermediary between raw data and business users. This system performs data cleaning, exploration, modeling, and interpretation automatically, eliminating the need for users to have specialized skills while providing consistent, reproducible insights without person-dependency
Solution Approach 2:
The system enables self-service data analysis by automatically executing the complete analytical workflow without human intervention. The system independently performs data preprocessing, selects appropriate analysis methods, executes models, and generates interpretations, allowing business users to obtain insights without requiring data science expertise
2Productivity
If data scientists are hired to analyze large volumes of data, then effective analysis can be performed, but data scientists are scarce and costly
Solution Approach 1:
The patent creates a computational copy of the data scientist's analytical capabilities through automated algorithms and machine learning models. The system replicates expert-level data analysis functions including data cleaning, exploration, modeling, and interpretation, making these capabilities widely accessible without requiring actual data scientists
Solution Approach 2:
The system transforms the analytical capability from a human-dependent resource to an automated computational process by changing the operational parameters from manual expert intervention to algorithmic execution. This enables scalable data analysis productivity independent of the quantity of skilled personnel available
3Loss of information
If business intelligence tools are used to display data, then data visualization is achieved, but the tools stop at displaying data and cannot provide interpreted insights
Solution Approach 1:
The system performs preliminary data processing and analysis actions automatically before presenting results to users. It pre-executes data cleaning, exploration, modeling, and interpretation tasks, so that when insights are delivered to business users, the complex analytical work has already been completed automatically in the background
Solution Approach 2:
The patent replaces the mechanical process of manual data interpretation with automated computational systems. Machine learning models and algorithms substitute for human analysts in performing data exploration, pattern recognition, and insight generation, enabling full automation of the interpretation process while maximizing information extraction
Data Source
AI summary
Embodiments of the invention provide systems and methods for generating natural language insights about a set of data. More specifically, embodiments of the present invention are directed to methods and systems that transform data into insights or actionable information. The output generated by embodiments of the present invention would be equivalent to that of an observation made or insights gathered by a qualified data scientist presented with the same data. Embodiments as described herein can include an insight engine that can analyze both structured and unstructured data and generate information in a natural language of the user's choice. Insights provided by embodiments described herein can be supported by an ability to drilldown to graphs/tables and atomic data and provide a good starting point for further analysis.