Interactive Data Analysis UI for Trillion-Row Query 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, with many iterations resulting in high costs.
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
Engineering Contradiction Analysis
1Quantity of substance
If traditional data exploration methods are used to analyze large volumes of data, then comprehensive data analysis can be performed, but the process becomes time and resource intensive with high consumption of computer memory and processing power
Solution Approach 1:
The patent segments the data analysis process into discrete, manageable nodes representing individual operations (filtering, aggregation, transformation). Each node processes data independently and can be executed separately, allowing the system to handle large data volumes without requiring all operations to run simultaneously, thus reducing peak resource consumption while maintaining comprehensive analysis capability.
2Loss of information
If traditional data exploration methods are used to locate discrete pieces of information, then thorough search can be performed, but the process requires many iterations resulting in high time costs
Solution Approach 1:
The patent applies preliminary action by pre-defining and storing data analysis nodes with their associated operations, filters, and transformations. These nodes are prepared in advance and can be quickly executed or modified during exploration, eliminating the need to build analysis logic from scratch during each iteration and significantly reducing the time required to locate discrete information while maintaining thorough search capability.
3Loss of information
If data analysis graphs with multiple nodes are created to maintain detailed analysis steps, then comprehensive tracking of analysis process is achieved, but the system complexity increases
Solution Approach 1:
The patent uses copying to create reusable node templates that can be instantiated multiple times in data analysis graphs. Instead of defining complex analysis logic from scratch for each operation, standard node types with predefined functionality are copied and configured with specific parameters, simplifying the creation and management of multi-node analysis graphs while maintaining comprehensive tracking of analysis steps.
Data Source
AI summary
The systems and methods described herein provide highly dynamic and interactive data analysis user interfaces which enable data analysts to quickly and efficiently explore large volume data sources. The data analysis 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, such as Internet proxy data, which may include trillions of rows of data. 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.