Hierarchical Data Versioning via Segmented Tables
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Solution Overview
Problem
Existing Master Data Management (MDM) systems face challenges in effectively managing and manipulating different versions of hierarchies and hierarchical data, particularly in maintaining data consistency and integrity across multiple users and systems.
Innovation Solution
The implementation of a system that allows for the creation, management, and visualization of hierarchy versions through user interfaces and business workflows, utilizing a three-tier client-server architecture with relational database management systems, where versioning is enabled by creating corresponding version tables with additional metadata and utilizing partitioning concepts for optimized data retrieval and deletion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If version tables are created to manage different versions of hierarchical data, then the ability to manage and manipulate multiple versions is improved, but the device complexity increases
Solution Approach 1:
The data management system is segmented into multiple version tables (e.g., version_0, version_1, version_2) that store different versions of hierarchical data. Each version table is an independent structure that can be managed separately, allowing the system to handle multiple versions without complicating the overall architecture. This segmentation enables version management while maintaining structural simplicity through modular design.
2Productivity
If partitioning concepts are used for optimized data retrieval and deletion, then the productivity is improved, but the device complexity increases
Solution Approach 1:
Data tables are partitioned into manageable segments based on version identifiers and hierarchical levels. This segmentation allows the system to retrieve and delete data in smaller, more efficient units rather than processing entire tables at once. The partitioning strategy optimizes performance by reducing the scope of operations while maintaining a straightforward implementation through consistent partitioning rules.
3Measurement precision
If metadata is added to version tables to track version information, then the measurement precision is improved, but the device complexity increases
Solution Approach 1:
Metadata fields serve as intermediaries between the version tables and the version control logic. These metadata fields (such as version identifiers, creation timestamps, and parent version references) provide precise tracking information without requiring complex version management mechanisms. The metadata acts as a simple mediator that enables accurate version tracking while keeping the overall structure straightforward.
Data Source
AI summary
A method, system, apparatus, and article of manufacture provide the ability to maintain multiple versions of structured views of data in a computer system. A relational database management system (RDBMS) is executed that stores master data in the computer system in master RDBMS tables. The master data is hierarchical in nature and hierarchy metadata for the master data is stored in the RDBMS tables. As part of a process and framework, a series of business rules and process workflows are maintained to manage the master data. Version tables are created in the RDBMS that correspond to each of the master RDBMS tables. Each of the version tables includes an attribute denoting version information. Versions of the master data are defined by replicating the master data and hierarchy metadata into the corresponding version tables. The version tables are used to graphically visualize, manage, and manipulate the versions of the master data.