Interactive Data Analysis UI for Fast Query Path Exploration

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Solution Overview

Problem

Exploration and analysis of large volumes of data is time and resource intensive, often requiring powerful processors and leading to insurmountable challenges in locating discrete pieces of information due to noisy data and the need for multiple iterations.

Innovation Solution

A dynamic and interactive data analysis system with features like breadcrumb and tree view UI controls, allowing users to navigate and save data analysis paths, and query optimization techniques to efficiently explore and filter data.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If users manually explore large volumes of data through multiple iterations, then they can locate discrete pieces of information, but the process becomes time and resource intensive

Engineering Contradiction:

Improveability to locate discrete informationVSAvoidtime required for data exploration

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system pre-generates multiple possible analysis paths and their corresponding results before the user needs them. When a user queries the system, the answer is already computed and stored in the data analysis graph, eliminating the need for iterative exploration and significantly reducing the time required to locate discrete information.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The data analysis graph dynamically adapts to user queries by providing pre-computed results for various possible analysis paths. The system transitions from static data storage to dynamic result delivery, where the graph structure and contents are optimized based on anticipated user needs and query patterns.

Inventive Principle:

Principle #15Dynamics

2Measurement precision

If users manually explore large volumes of data through multiple iterations, then they can locate discrete pieces of information, but resource consumption increases

Engineering Contradiction:

Improveability to locate discrete informationVSAvoidcomputational resource consumption

Core Design Contradiction:

Measurement precisionVSUse of energy by moving object

Solution Approach 1:

The system performs computationally intensive data analysis operations in advance and stores the results in the data analysis graph. When users query the system, they receive pre-computed answers rather than triggering new iterative analysis processes, dramatically reducing real-time computational resource consumption while maintaining the ability to locate discrete information.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system creates and maintains copies of analysis results in the data analysis graph for various possible query paths. Instead of re-computing results when users query, the system retrieves pre-stored copies of the analysis results, reducing computational resource usage while providing accurate information location.

Inventive Principle:

Principle #26Copying

3Adaptability or versatility

If the data analysis graph contains all possible analysis paths, then query results are comprehensive, but the graph size and complexity increase

Engineering Contradiction:

Improvecomprehensiveness of query resultsVSAvoiddata analysis graph size

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The data analysis graph is segmented into multiple independent or semi-independent path components. Each segment represents a specific analysis path from root to leaf nodes. This segmentation allows the system to manage large numbers of analysis paths by organizing them into discrete, manageable units that can be stored, retrieved, and updated independently.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The data analysis graph uses a nested hierarchical structure where parent nodes contain child nodes, and each node can contain multiple analysis paths. This nesting allows comprehensive coverage of all possible analysis paths while organizing them in a compact, space-efficient manner that reduces overall graph complexity compared to a flat structure.

Inventive Principle:

Principle #7Nested doll (Nesting)

Data Source

PatentUS20260016946A1Interactive user interface for dynamically updating data and data analysis and query processing

Publication Date: 2026.01.15 PALANTIR TECHNOLOGIES INC

AI summary

Data analysis system with highly dynamic and interactive data analysis user interfaces which enable data analysts to quickly and efficiently explore large volume data sources. The system enables the user to investigate large volumes of data over many different paths of analysis while maintaining detailed and retraceable steps taken by the user over the course of an investigation, as captured via the user's queries and user interaction with the user interfaces provided by the data analysis system. Data analysis paths may involve exploration of high volume data sets. The data analyst may pursue a data analysis path that involves, among other things, applying filters, joining to other tables in a database, viewing interactive data visualizations, and so on. The data analysis system enables a user to refresh or insert a node in a workflow. The data analysis system further provides data editing, reporting, enrichment, expression language, and charting functionality.