Dynamic Data Artifact Instances for Flexible Access
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Solution Overview
Problem
Existing data access systems face limitations in flexibility when accessing data from diverse sources, as they often rely on static data models that do not account for varying data storage formats and schema differences across different systems, leading to complications in data access and source structuring.
Innovation Solution
The implementation of multiple data artifact instances that can access different data sources, with switching logic to determine the appropriate instance for a data access request, allowing for dynamic and flexible data access methods such as federation and replication, and the use of logical pointers that can be updated to point to different data sources based on performance or availability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a static data model is used to access data from diverse sources, then the system structure is simple and easy to implement, but the flexibility and adaptability to different data storage formats and schema differences are limited
Solution Approach 1:
The patent segments the data access system into multiple independent data artifact instances, each capable of accessing different data sources with specific formats and schemas. This segmentation allows the system to handle diverse data sources without requiring a complex unified structure, as each instance can be optimized for its specific data source while maintaining overall system flexibility.
Solution Approach 2:
The patent creates data artifact instances that serve multiple functions - each instance can access different data sources (relational databases, cloud systems, file systems) with different formats and schemas. This multi-functionality allows a single instance type to handle various data access scenarios, improving adaptability without proportionally increasing system complexity.
2Adaptability or versatility
If multiple data artifact instances are created to access different data sources, then data access flexibility and adaptability are improved, but the complexity of managing and selecting the appropriate instance increases
Solution Approach 1:
The patent introduces switching logic as an intermediary component that manages the selection between multiple data artifact instances. This mediator automatically determines which instance to use based on the data access request characteristics, eliminating the need for users to manually manage instance selection and reducing operational complexity despite having multiple instances.
Solution Approach 2:
The switching logic employs feedback mechanisms to monitor data access requests and automatically select the appropriate data artifact instance based on current system state, data source characteristics, and performance metrics. This feedback-driven selection process simplifies operation by making instance selection automatic rather than manual.
3Reliability
If data is stored in multiple locations with different formats and schemas, then data availability and access methods are improved, but the difficulty of detecting and measuring the appropriate data source increases
Solution Approach 1:
The patent uses metadata tags and identifiers (analogous to color changes) to mark and differentiate various data sources, formats, and schemas. These metadata markers make it easier to detect and identify the appropriate data source by providing clear, distinguishable characteristics for each data artifact instance, reducing the difficulty of data source detection despite multiple storage locations.
4Productivity
If static data models are used, then the system is easier to implement and maintain, but the data access speed and performance optimization are limited
Solution Approach 1:
The patent transitions from static data models to dynamic data artifact instances that can adapt their access methods based on current performance requirements and data source characteristics. Each instance can be configured with optimization parameters for its specific data source, enabling faster data access while maintaining manageable complexity through the use of standardized instance templates and automated configuration.
Data Source
AI summary
Techniques and solutions are described for providing flexible access to data during execution of a data access request. Multiple instances of a data artifact are created, where different instances of the data artifact provide access to different data sources having data associated with the data access request. When a data access request is executed, a particular data artifact instance can be used during execution of the data access request. In some cases, switching logic can be used to determine which data artifact instance is to be used in executing the data access request. Also described are technologies for facilitating creation of data artifact instances corresponding to a modelling artifact.