Data View Portion Copying for Analysis Space Context Retention
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Solution Overview
Problem
In large and complex relational databases, users face challenges in isolating and visualizing relevant data subsets for analysis and collaboration, as the significance of critical data can be obscured within vast datasets, requiring manual and time-consuming steps to filter out non-relevant information and lacking clear context for discussion.
Innovation Solution
A method and apparatus that transform and copy a selected data view portion, including associated context information, to a separate analysis space, allowing users to easily isolate and share relevant data by clicking and dragging subsets, while retaining metadata and formatting for further access, thus simplifying data visualization and collaboration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If users manually manipulate and delete non-relevant columns, rows, and cells to highlight relevant data subsets, then the relevance of data can be emphasized, but the process becomes time-consuming and complex
Solution Approach 1:
The system segments the data view into selectable portions, allowing users to isolate and copy only the relevant subsets needed for analysis. This segmentation enables focused work on specific data portions without manually manipulating the entire dataset, reducing time while preserving context through the copying mechanism.
Solution Approach 2:
The system copies selected data view portions to analysis spaces, creating reusable representations of relevant data subsets. This copying approach eliminates the need for manual deletion and manipulation operations, significantly reducing the time required to prepare data for analysis while maintaining the original context and structure.
2Ease of operation
If users separate relevant data portions from larger visualizations, then the focus on critical data improves, but the context of the selection becomes less apparent
Solution Approach 1:
The analysis space acts as an intermediary between the original data view and the user's analysis work. When data portions are copied to this intermediate space, they maintain their contextual relationships and structure, allowing users to work with isolated data while preserving the context needed for accurate interpretation.
3Measurement precision
If collaboration panels display detailed data portions, then analysis precision improves, but the limited space becomes insufficient for effective collaboration
Solution Approach 1:
The system segments data presentation into two forms: detailed data view portions for precise analysis and simplified character representations for space-constrained collaboration panels. This segmentation allows the collaboration panel to display essential information in a compact format while maintaining access to detailed views when needed, preserving both precision and space efficiency.
Data Source
AI summary
Embodiments relate to transforming data views for analysis and/or collaboration purposes. An original data view is displayed on a document page in response to a database query. A filter operation is performed by selecting a specific subset of that original data view. A copy of that transformed data view portion including a tuple, is displayed in a separate analysis space (e.g., on the same document page, on another page, or within a collaboration panel). In one example, a user clicks/drags a subset of a table data view for transformation and copying. When the selected and transformed data view portion is copied to the analysis space, relevant associated context information (e.g., the underlying query, measures, dimensions, chart legends, formatting) may be retained for later access. To conserve the limited space typically available to a collaboration panel, certain embodiments may simplify presentation by reproducing only the characters of the transformed data portion.