Query-Based Sparklines Without Spreadsheet Data Import
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Solution Overview
Problem
Conventional spreadsheet applications require data importation to generate sparklines, leading to inefficient resource usage and lack mechanisms for modifying or replicating sparklines without manipulating underlying data, and they do not support real-time data updates or efficient handling of large datasets.
Innovation Solution
An improved spreadsheet application generates and manipulates data visualizations like sparklines by referencing data descriptions stored in cells, transmitting queries to external data stores for data retrieval, and rendering visualizations without storing the actual data, allowing for efficient resource use and dynamic updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If data is imported into cells to generate sparklines, then sparklines can be generated and displayed, but file size increases and resource consumption increases
Solution Approach 1:
The patent extracts the actual data from the spreadsheet file by storing it in an external data store, keeping only data descriptions (queries) in the file. This separation allows sparklines to be generated without importing actual data into cells, thereby reducing file size while maintaining sparkline generation capability.
Solution Approach 2:
The patent introduces data descriptions as an intermediary between the spreadsheet application and the external data store. These data descriptions act as mediators that enable sparkline generation by referencing external data without storing the actual data in the file, thus resolving the contradiction between generation capability and file size.
2Ease of manufacture
If data is imported into cells to generate sparklines, then sparklines can be generated, but resource consumption increases
Solution Approach 1:
The patent extracts data from the local file environment and stores it externally, eliminating the need to load and process large datasets in memory when generating sparklines. This extraction reduces resource consumption while maintaining the ability to generate sparklines on demand.
Solution Approach 2:
The patent uses data descriptions as lightweight copies that reference external data. Instead of copying actual data into cells for sparkline generation, the system uses compact query descriptions that point to external data sources, significantly reducing memory and computational resources required.
3Ease of manufacture
If data is stored in cells for sparkline generation, then sparklines can be created, but modification and replication require manipulating underlying data
Solution Approach 1:
The patent segments the sparkline creation process into two independent parts: data descriptions (stored in cells) and actual data (stored externally). This segmentation allows users to modify and replicate sparklines by working with lightweight data descriptions rather than manipulating large underlying datasets, greatly improving ease of operation.
Solution Approach 2:
The patent enables easy replication of sparklines by allowing users to copy data descriptions between cells. Since data descriptions are compact query definitions rather than actual data, copying them is efficient and does not involve duplicating large datasets, making replication straightforward.
4Ease of manufacture
If data is imported into cells, then conventional sparkline generation works, but real-time data updates are not supported
Solution Approach 1:
The patent makes the data source dynamic by using query-based data descriptions that can reference external data stores in real-time. Instead of static imported data, the system dynamically retrieves data when sparklines are generated or updated, enabling real-time update capability while maintaining sparkline generation functionality.
Solution Approach 2:
The patent uses data descriptions as intermediaries that facilitate real-time updates. These descriptions act as dynamic references to external data sources, allowing the system to adapt to changing data without requiring data re-importation, thus enabling real-time update capability.
Data Source
AI summary
Various systems and methods are described herein for an improved spreadsheet application that allows a user to generate, manipulate, and replicate data visualizations (e.g., sparklines, graphs, charts, etc.) using functions without importing data into cells of the application. For example, data is stored in one or more remote or local data stores accessible to the improved spreadsheet application. A user enters a function into a cell of the improved spreadsheet application. The improved spreadsheet application generates a query using the function, the query identifying a portion of a dataset to retrieve from the data store(s). The improved spreadsheet application then transmits the query to the data store(s) and retrieves the requested data. A renderer of the improved spreadsheet application then renders a sparkline using the retrieved data. The improved spreadsheet application displays the rendered sparkline in the cell in which the function was entered, or at another designated location.