Denormalized Data Object With Supplemental Attributes For Localization
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Solution Overview
Problem
The complexity and time-consuming nature of localizing data objects for specific jurisdictions in software applications, particularly in heavily regulated areas like financial reporting and taxation, due to the need for jurisdiction-specific data and calculations.
Innovation Solution
Storing supplemental localization attributes in a separate data object, rather than integrating them into core data model objects, allowing for efficient retrieval and management of localization data across multiple jurisdictions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If core data model objects are modified to include jurisdiction-specific attributes, then localization capability is improved, but device complexity increases
Solution Approach 1:
The patent segments the data model into core data model objects that remain unchanged and supplemental data objects that contain jurisdiction-specific attributes. This segmentation allows localization without modifying the core data model, thus maintaining simplicity while improving adaptability.
Solution Approach 2:
The patent extracts jurisdiction-specific attributes from the core data model objects and places them in separate supplemental data objects. This extraction removes the source of complexity from the core model while preserving the ability to localize data for different jurisdictions.
2Adaptability or versatility
If core data model objects are modified for each jurisdiction, then localization capability is improved, but loss of time increases
Solution Approach 1:
The patent creates supplemental data objects in advance that contain jurisdiction-specific attributes. These supplemental objects are prepared separately and can be quickly associated with core data model objects when localization is needed, eliminating the time-consuming process of modifying core models for each jurisdiction.
3Loss of information
If jurisdiction-specific data is integrated into core data model objects, then data completeness is improved, but computing resource usage increases
Solution Approach 1:
The patent merges core data model objects with supplemental data objects through associations, allowing the system to access both core and jurisdiction-specific attributes as a unified data set. This merging provides data completeness while keeping the supplemental data separate to conserve computing resources.
4Adaptability or versatility
If core data model objects are modified to include all possible jurisdictional attributes, then adaptability is improved, but device complexity increases
Solution Approach 1:
The patent implements a dynamic data model where supplemental data objects can be selectively associated with core data model objects based on the specific jurisdiction and data retrieval needs. This dynamic approach provides jurisdictional adaptability without permanently increasing the complexity of the core data model structure.
Data Source
AI summary
The present disclosure provides techniques and solutions for storing data in a way that facilitates the update and creation of data models, as well as conserving computing resources when accessing such data. A number of data objects can be included in a data model, such as a core data model that can be used in various jurisdictions. A supplemental data object is created that includes data relevant to data objects in the data model. For example, the supplemental data object can include localization attributes. The supplemental data object can be considered as denormalized. A request for data can retrieve data from a data object in the data model, as well as data in the supplemental data object. Different sets of attributes can be retrieved from the supplemental data object based on a type associated with a data request for a data model object.