Database Audit via XML State Comparison
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Solution Overview
Problem
Conventional audit systems for relational databases are inefficient and limited in tracking changes across multiple tables, often requiring detailed knowledge of the database structure and relationships, and struggle to correlate changes between different states of the database.
Innovation Solution
A system that generates and compares XML documents representing pre-change and post-change states of a database object, eliminating the need to mine multiple tables by capturing changes in a single document, allowing for efficient tracking and display of differences without requiring knowledge of the data model or table structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional audit systems mine multiple database tables to track changes, then they can examine database development over time, but the process becomes computationally expensive and inefficient
Solution Approach 1:
The patent merges data from multiple database tables into a single normalized representation. By consolidating purchase order data, line item data, and related table data into one unified structure, the system eliminates the need to mine multiple tables separately, thereby reducing computational expense while maintaining complete audit information
Solution Approach 2:
The patent creates a normalized copy of the database object that represents the complete state of the object independent of the underlying table structure. This copy can be generated efficiently and compared across time periods without repeatedly querying the complex multi-table database structure
2Reliability
If conventional audit systems require knowledge of database structure and relationships, then they can effectively audit database objects, but the system complexity increases and adaptability decreases
Solution Approach 1:
The patent extracts the audit functionality from the database structure itself. Instead of requiring the audit system to understand complex table relationships and data models, the system extracts a simplified normalized representation of the database object that can be audited independently of the underlying database structure
Solution Approach 2:
The normalized representation serves multiple functions: it represents the database object state, enables change tracking, and provides audit information all without requiring knowledge of the original database structure. This universal representation works across different database schemas and table configurations
3Stability of the object's composition
If conventional relational databases store data across multiple tables, then they maintain data relationships and structure, but correlating changes between database states becomes difficult or impossible
Solution Approach 1:
The patent segments the database object into a normalized structure that separates the object's logical components from its physical table storage. This segmentation allows the system to track changes in the logical object state without being constrained by the relational table structure, making change correlation straightforward while preserving data integrity
Data Source
AI summary
Systems, methods, and other embodiments associated with database auditing are described. One example method includes generating a first extensible markup language (XML) document using data from a database object. A database object may include data from multiple relational data tables. The method includes generating a second XML document in response to an event causing a change to the database object. The method also includes comparing the first and second XML documents to identify changed values. The method also includes displaying the identified changes.