Multi-dimensional Data Insight Interaction System
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Solution Overview
Problem
Data exploration in multi-dimensional datasets is inefficient due to the large exploration space and lack of user guidance, leading to labor-intensive manual slicing-and-dicing and unidirectional interactions between users and tools, resulting in missed insights.
Innovation Solution
A computing device provides an interface that allows users to visualize insights mined from multi-dimensional data by selecting a dataset or a portion of a visualization, presenting manually and automatically-created insights related to data subspaces, and automatically guiding the analysis flow to quickly discover desirable insights.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual slicing-and-dicing is used to explore multi-dimensional data, then users can customize their analysis, but the process becomes labor-intensive and time-consuming
Solution Approach 1:
The system pre-computes and stores insights, aggregations, and patterns in the database before users need them. When a user queries the data, the system retrieves pre-computed insights rather than calculating everything from scratch, dramatically reducing analysis time while maintaining the ability to customize views through user selections.
Solution Approach 2:
The system automatically generates insights, visualizations, and analysis results without requiring manual slicing-and-dicing operations. The database self-services by providing pre-computed multi-dimensional insights that users can directly consume and interact with, eliminating the labor-intensive manual data manipulation process.
2Adaptability or versatility
If users manually specify visualizations for data exploration, then they can control the analysis focus, but they may miss useful insights and spend vast amounts of time
Solution Approach 1:
The system provides feedback by automatically generating and presenting multiple relevant insights, visualizations, and analysis results based on user queries. Instead of users having to manually specify every visualization, the system responds with curated insights that adapt to user interests while simultaneously exposing additional useful insights the users might not have discovered otherwise.
Solution Approach 2:
The system serves multiple functions simultaneously: it provides users with customized visualizations based on their selections while also automatically generating and presenting additional relevant insights. This multi-functional approach allows users to maintain control over their analysis focus while the system complements their exploration with automatically discovered patterns and insights.
3Device complexity
If the interaction between data tools and users is unidirectional, then the system is simple to implement, but users cannot efficiently discover insights
Solution Approach 1:
The system implements bidirectional interaction where the database not only receives user queries but also actively responds with pre-computed insights, suggestions, and visualizations. This feedback loop enables efficient insight discovery as the system guides users toward important patterns while users maintain control through their selections and queries.
Solution Approach 2:
The system introduces an intermediary layer of pre-computed insights and analysis results between the raw data and the user. This intermediary layer facilitates efficient bidirectional interaction by translating user queries into relevant insights while also presenting discovered patterns back to users in an accessible format, thereby improving productivity without excessive complexity.
Data Source
AI summary
A computing apparatus of an insight interfacing system receives from a user a request for a dataset comprising a plurality of subspaces of a multi-dimensional data structure. Insights are received based on the received request then presented on a display device. Also, a chart may be presented based on the received request. The computing apparatus receives a selection of at least a portion of the presented one or more insights or a portion of the chart, then receives contextual insights based on the selected portion and presents the contextual insights on the display device.