Data Object Generation via Template Variable Mapping
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Solution Overview
Problem
Conventional mechanisms for performance-based data analysis in cloud platforms are manually intensive, error-prone, and time-consuming, requiring users to import, process, and format data before sharing, which is inefficient and prone to errors.
Innovation Solution
A data service that automates the process of importing, processing, and transferring data by allowing users to upload templates to a shared dataspace, where a data service generates dynamic content items by mapping data fields to template variables, reducing manual interaction and errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users manually import, process, and format data before sharing, then data can be shared with other users, but the process becomes manually intensive, repetitive, and error-prone
Solution Approach 1:
The system performs preliminary actions by automatically importing data from the database, processing it through the second template, and formatting it before it reaches the user. The data service pre-processes the data object by mapping fields to template variables, so when users want to share data, it is already prepared and formatted, eliminating manual preprocessing time
Solution Approach 2:
The data service enables self-service by automatically handling the entire data processing workflow. The system serves itself by importing data, processing it through templates with variable mappings, and generating formatted outputs without requiring manual user intervention for each step, thus reducing both time consumption and manual effort
2Ease of operation
If users manually import, process, and format data before sharing, then data can be shared with other users, but the process becomes error-prone
Solution Approach 1:
The system performs preliminary validation and processing actions automatically before data sharing. The data service pre-processes the data object by mapping fields to template variables according to predefined rules, ensuring data integrity and correctness before it reaches the user, thereby reducing errors
Solution Approach 2:
The data service enables self-service by automatically handling the entire data processing workflow with consistent, rule-based operations. The system serves itself by importing data, processing it through templates with variable mappings, and generating formatted outputs without requiring manual user intervention, thus eliminating human errors from the process
3Productivity
If a data service automates the process of importing, processing, and transferring data, then efficiency is improved and manual interaction is reduced, but the system complexity increases
Solution Approach 1:
The data service acts as an intermediary between the database and the user interface. It automatically imports data from the database, processes it through templates with variable mappings, and generates formatted outputs. This intermediary layer handles the complexity of data processing internally, presenting a simple interface to users while maintaining high productivity
Solution Approach 2:
The system segments the data processing workflow into distinct, manageable components: data import from database, template processing with variable mapping, and output generation. Each component is handled separately by the data service, making the overall complex process modular and maintainable while achieving high automation and productivity
Data Source
AI summary
Methods, systems, and devices for data object generation are described. A data service may receive an application programming interface (API) request that indicates a first template, a second template, a data set, and one or more user identifiers. The data service may retrieve the first template and the second template from a template library in response to the API request. The data service may generate a data object based on importing fields from the data set to the second template and linking the second template to the first template in accordance with a mapping between variables in the first template and the fields from the data set. The data service may transmit an API response that includes an identifier of the data object that is accessible to the one or more user identifiers.