Spreadsheet Formulas for Ordered External Data Retrieval
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Solution Overview
Problem
Existing spreadsheet applications struggle with handling large, complex, and inconsistent data sets, requiring users to inspect and fix data before performing complex operations, and lack ease in handling diverse data sets and correcting inconsistencies or missing data.
Innovation Solution
A spreadsheet application that allows users to handle complex data inter-relationships through ordered data commands, enabling easy data retrieval and usage within cells, supporting formulaic handling of non-spreadsheet cell data, and facilitating consistent calculations and data presentation with row and column headings, while allowing for easy drill-down and drill-up capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users manually inspect and fix data before performing operations, then data accuracy is improved, but time consumption increases
Solution Approach 1:
The system performs preliminary data cleaning and transformation actions automatically before the user performs analysis operations. The ordered data commands sequence data retrieval and usage, pre-processing complex data inter-relationships and inconsistencies so they are resolved before the user needs to perform calculations or analysis.
Solution Approach 2:
The spreadsheet application handles data inconsistencies and missing data automatically through its ordered data commands and formulaic handling capabilities. The system self-corrects data issues without requiring manual user intervention to inspect and fix each data problem individually.
2Reliability
If users manually inspect and fix data, then data consistency is improved, but ease of operation deteriorates
Solution Approach 1:
The application automatically handles data consistency issues through its ordered data commands that sequence data retrieval and usage. The system self-manages data consistency by processing complex data inter-relationships and correcting inconsistencies automatically, eliminating the need for users to manually inspect and fix data.
Solution Approach 2:
The ordered data commands act as an intermediary layer between the user and the complex data. This intermediary sequences and manages data retrieval and usage, handling data consistency and inter-relationships automatically without requiring users to directly manipulate or inspect the underlying data structure.
3Adaptability or versatility
If users work with diverse data sets, then adaptability is improved, but device complexity increases
Solution Approach 1:
The spreadsheet application provides universal handling capabilities for diverse data sets through its ordered data commands and formulaic functions. The same command structure works for all types of data (alpha, numeric, alphanumeric, date/time) whether keyed or not, and whether normalized or de-normalized, eliminating the need for different approaches for different data types.
Solution Approach 2:
The system segments data handling into discrete ordered commands that sequence data retrieval and usage. This segmentation allows complex data inter-relationships to be managed through a series of simple, ordered operations rather than requiring complex unified processing, making the system more manageable despite its versatility.
4Productivity
If users handle complex data inter-relationships, then productivity is improved, but ease of operation deteriorates
Solution Approach 1:
The ordered data commands perform preliminary sequencing of data retrieval and usage before the user performs analysis. This pre-sequencing handles complex data inter-relationships automatically, allowing users to focus on productivity-enhancing analysis rather than manually managing data relationships.
Solution Approach 2:
The application self-manages complex data inter-relationships through its formulaic handling and ordered commands. The system automatically processes data retrieval, sequencing, and relationship management, enabling users to maintain high productivity without the operational burden of manually handling complex data structures.
Data Source
AI summary
The technology disclosed relates to accessing external data, including massive amounts of data stored in the cloud, in spreadsheet cells: accessing external data direct via a formulaic variable in a spreadsheet, specifying an ordered progression for the accessed external data, selectively propagating data accessed using the formulaic variable vertically or horizontally, within a propagation pattern responsive to normal A$1, $A1 and $A$1 spreadsheet conventions. Two or more external data fields, responsive to the formulaic variable, have an ordered sequence relationship that nests ordering of vectors of the propagated data; and the ordering according to the ordered sequence relationship is maintained during replication by copy and paste. In another disclosed method, the external data is generated using an implicit join of data from at least two external data sources to generate multiple adjoining vectors of spreadsheet cells of data responsive to selection parameters in the formulaic variable.