Hybrid Data Table Visualization Across Multiple Memory Regions
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Solution Overview
Problem
Analyzing large data sets is computationally intensive and time-consuming, and existing methods struggle to efficiently locate relevant data across voluminous databases, limiting user productivity and data accessibility.
Innovation Solution
The method involves defining data tables with associated fields across multiple memories, enabling visualization and analysis of data sets while allowing seamless blending of in-memory and external data, using a hybrid approach that links data sources without the need for extensive data loading, thereby facilitating transparent and unified data management and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If large data sets are loaded into memory for analysis, then data accessibility and analysis capability are improved, but memory resource consumption and processing time increase
Solution Approach 1:
The patent divides the data management system into multiple memory regions (first memory and second memory) that can store different portions of data sets. This segmentation allows the system to handle large data volumes by distributing them across multiple memory locations, thereby improving data accessibility without requiring a single large memory block that would consume excessive resources.
Solution Approach 2:
The patent introduces a multi-dimensional memory architecture by utilizing both first memory and second memory to store data portions. This dimensional expansion of memory usage enables the system to access and analyze large data sets efficiently by distributing data across multiple memory dimensions, thus improving productivity without linearly increasing resource consumption in a single dimension.
2Loss of information
If data from multiple sources are integrated for comprehensive analysis, then data completeness and insight quality are improved, but system complexity and data integration overhead increase
Solution Approach 1:
The patent creates a universal data management system that can handle multiple data sources and formats through a unified architecture. The system provides common data access and analysis capabilities across different memory regions and data types, thereby ensuring data completeness while avoiding the complexity of multiple separate systems through multi-functionality.
Solution Approach 2:
The patent introduces an intermediary data management layer that facilitates integration between first memory and second memory, as well as between different data sources. This intermediary layer handles data association, retrieval, and coordination, thereby ensuring complete data integration while reducing overall system complexity by centralizing integration logic.
3Manufacturing precision
If extensive data is loaded and processed, then analysis comprehensiveness is improved, but processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary actions by pre-loading and organizing data portions in both first memory and second memory before analysis is needed. Data is pre-associated and structured in a manner that facilitates quick retrieval and analysis, thereby improving analysis comprehensiveness while reducing actual processing time when queries are executed.
Solution Approach 2:
The patent enables continuous data access and analysis operations by maintaining data in an easily accessible format across multiple memory regions. The system supports ongoing analysis without requiring repeated data loading or processing interruptions, thereby achieving comprehensive analysis with reduced processing time through continuous operational capability.
Data Source
AI summary
Systems and methods for data management are disclosed. One method can comprise defining a plurality of data tables, wherein one or more of the data tables comprises a data field, loading a first data table of the plurality of data tables in a first memory, wherein one or more data fields of the first data table is associated with a second data table of the plurality of data tables, and wherein the second data table is resident in a second memory, and presenting a visualization of the first data table and the second data table.