Tagged Column-Oriented Data Structures for Faster Project Data Filtering
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Solution Overview
Problem
Existing project management software lacks efficient data searching capabilities, particularly in filtering and aggregating relevant data elements, leading to inefficiencies in managing projects.
Innovation Solution
A system and method for generating tagged column-oriented data structures, where columns contain cells of a single data type, including at least one tag type column, allowing for rapid data location and filtering based on tags.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional project management software is used, then basic project management functions are provided, but data searching and filtering capabilities are inefficient
Solution Approach 1:
The patent segments data into column-oriented structures where each column represents a specific data type (e.g., tags, dates, numbers). This segmentation allows the system to efficiently filter and search specific columns independently, improving data searching efficiency while maintaining ease of operation through structured organization.
Solution Approach 2:
The patent introduces tags as intermediary elements that mediate between data elements and search queries. Tags serve as a intermediary layer that enables efficient filtering and aggregation of data without requiring complex search operations, thus improving both productivity and ease of operation.
2Loss of time
If data is stored in traditional formats, then data can be stored, but relevant data cannot be quickly located and filtered
Solution Approach 1:
The patent divides data into segmented columns where each column is optimized for specific data types. This segmentation enables rapid retrieval of relevant data by directly accessing specific columns rather than searching through entire datasets, significantly reducing data retrieval time while keeping the structure manageable.
Solution Approach 2:
The patent implements preliminary organization of data into pre-defined column structures with appropriate data types before data entry. This preliminary structuring eliminates the need for complex filtering operations during retrieval, reducing both time loss and operational complexity.
3Loss of information
If comprehensive data fields are included, then data completeness is improved, but data visibility and understanding are reduced
Solution Approach 1:
The patent segments comprehensive data into distinct columns, each with a specific purpose and data type. This segmentation maintains data completeness by preserving all information while improving visibility by organizing it in a structured manner that is easier to interpret and work with.
Solution Approach 2:
The patent applies local quality by giving each column specific characteristics appropriate to its data type (e.g., tags for categorization, dates for temporal filtering). This localized optimization maintains overall data completeness while enhancing visibility and ease of operation for specific data elements.
Data Source
AI summary
A system and method for generating tagged column-oriented data structures, including: generating a column-oriented data structure that comprises a plurality of columns, wherein each column comprises a plurality of cells that are associated with a single data type, wherein at least one of the plurality of columns is a tag type column; and inserting at least one tag into a first cell of the tag type column, where the first cell further associated with a first row of cells.