In-Memory Database Configurable Rules for GRC Monitoring
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Solution Overview
Problem
Current systems face challenges in efficiently analyzing large volumes of business data to identify compliance and other issues, particularly in a manner accessible to ordinary business users, and struggle to leverage the processing power available in in-memory databases for real-time monitoring and analysis.
Innovation Solution
The implementation of configurable rules within an in-memory database system, utilizing the high processing power of the database engine, allows for automatic monitoring and analysis of large data volumes through an analysis engine that communicates with the database engine to execute logic and identify issues such as those related to Governance, Risk, and Compliance (GRC), leveraging technologies like ABAP Database Connectivity (ADBC) and SAP HANA in-memory databases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional database systems are used to analyze large volumes of business data, then data analysis capability is provided, but processing time is excessive and performance issues occur
Solution Approach 1:
The patent changes the fundamental parameter of data storage location by moving data from disk-based conventional databases to in-memory databases. This parameter change transforms the processing speed from seconds/minutes to milliseconds, directly resolving the contradiction between data analysis capability and processing time.
2Measurement precision
If more processing power is allocated to analyze large data volumes, then analysis accuracy improves, but system complexity and resource requirements increase
Solution Approach 1:
The in-memory database system provides self-service capabilities where the database engine automatically executes configurable rules and performs analysis without requiring complex external processing systems. This reduces system complexity while maintaining high analysis accuracy through the database's inherent processing power.
3Ease of operation
If manual monitoring methods are used to identify compliance issues, then issue detection is possible, but the process is not accessible to ordinary business users and requires significant time
Solution Approach 1:
The patent introduces an intermediary layer consisting of configurable rules and analysis templates that enable ordinary business users to perform complex compliance monitoring without needing specialized technical knowledge. This intermediary simplifies the interface while maintaining powerful analysis capabilities, making the system accessible to non-technical users.
4Reliability
If comprehensive data analysis is performed to identify all compliance issues, then detection completeness improves, but processing time and computational resources increase significantly
Solution Approach 1:
The patent segments the comprehensive analysis into configurable rule-based components that can be executed independently and in parallel. This segmentation allows the system to maintain complete detection coverage while improving throughput by processing different compliance aspects simultaneously through the high-speed in-memory database engine.
Data Source
AI summary
Embodiments relate to the implementation of configurable rules that automatically monitor large volumes of data stored in a database. Certain embodiments may leverage the high processing power available to the database engine of an in memory database, in order to perform analysis of large data volumes for compliance and other purposes. Particular embodiments may utilize ABAP Database Connectivity (ADBC) to a HANA in memory database available from SAP AG, in order to implement and execute configurable rules in connection with governance, risk, and compliance (GRC) of large volumes of data stored therein. In various embodiments, an analysis engine in the application layer may rely upon the in memory database engine to execute at least some logic of the configurable rules.