Mapping Data Structures for Cross-System Accessibility
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Solution Overview
Problem
Existing data structures tailored for one context can limit accessibility of stored information in other contexts, as they may impair querying and data analysis, and can hinder access by different systems due to their specific parameters.
Innovation Solution
The system maps a first data storage schema to a second, generating a star data storage schema that includes a fact table and a dimension table, with the ability to resolve and combine tables, using surrogate identification tables and text tables to ensure time-relevant and time-irrelevant attributes are appropriately mapped, facilitating data processing across different systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data structures are tailored for operational efficiency in one context, then operational effectiveness is improved, but accessibility of stored information in other contexts deteriorates
Solution Approach 1:
The patent segments data storage into multiple data structures, each optimized for specific contexts. Instead of using a single tailored data structure, the system divides information into separate structures (e.g., transactional data structures for rapid transactions, analytical data structures for querying) that can be independently optimized and accessed based on the specific operational context needed.
2Speed
If data structures are optimized for rapid transactions, then transaction speed is improved, but querying and data analysis performance deteriorates
Solution Approach 1:
The patent implements dynamic data structure selection and transformation capabilities. The system can dynamically choose which data structure to access based on the operation type, and can dynamically transform data between structures. For example, transactional data is stored in an optimized structure for fast writes, while analytical queries dynamically access and transform the same underlying data into appropriate analytical structures without sacrificing transaction performance.
3Productivity
If data structures are tailored to parameters required by a first system, then operational efficiency for the first system is improved, but access to stored information by a second system deteriorates
Solution Approach 1:
The patent creates universal data storage mechanisms that can serve multiple systems with different parameter requirements. The system implements a unified data storage layer that can be accessed by multiple systems, each with their own optimized views. The universal structure allows the first system to access data in its optimized format while the second system simultaneously accesses the same data in its own optimized format, eliminating the need to choose between systems.
Data Source
AI summary
A first data storage schema in which a characteristic in a first dimension table is mapped by a first table and a second table can be received and a second data storage schema can be received. The first table maps the characteristic to a first object that include attributes to which time information is irrelevant to data processing activities and the second maps the characteristic to a second object that includes attributes to which time information is relevant to data processing activities. The second data storage schema includes a fact table including at least some facts drawn from the first data storage schema and a second dimension table that includes at least some characteristics drawn from at least one of the first object and the second object.