Sensitive Data Integration Toolkit for Enterprise Database Compliance
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Solution Overview
Problem
Current sensitive data protection technologies lack a cost-efficient integration solution to seamlessly integrate with enterprise operational databases, leading to high financial burdens, tech-debt, and implementation challenges, particularly in industries like finance, banking, healthcare, and retail, hindering compliance with standards such as HIPAA and SOX.
Innovation Solution
A cost-effective integration software-toolkit with four core components (Discovery, Qualifier, Resolution, and Control-Cube) using API-based microservices, REST APIs, and reactive AI, enabling seamless integration with enterprise databases and business use cases, ensuring compliance and reducing tech-debt through automation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If enterprises create their own extension systems to integrate sensitive data protection technologies with enterprise core systems, then integration capability is achieved, but financial burden increases enormously
Solution Approach 1:
The patent introduces a vendor-provided integration toolkit as an intermediary layer between sensitive data protection technologies and enterprise core systems. This pre-built toolkit includes pre-configured connectors, adapters, and integration patterns that enable seamless integration without requiring enterprises to develop custom extension systems, thereby eliminating the enormous financial burden while maintaining full integration capability.
Solution Approach 2:
The integration toolkit is designed as a universal solution that can integrate with multiple enterprise core systems, databases, and platforms through standardized interfaces and abstracted connection patterns. This multi-functional toolkit serves various integration scenarios (on-premises, cloud, hybrid) and supports different data protection implementations, eliminating the need for separate extension systems for each integration requirement.
2Adaptability or versatility
If high numbers of extension systems are created to integrate sensitive data protection technologies, then integration coverage is improved, but tech-debt increases and production support costs increase
Solution Approach 1:
The integration toolkit is segmented into modular, independently deployable integration patterns and connection templates that can be selectively applied to different enterprise systems. Each module is self-contained with documented integration patterns, allowing enterprises to adopt only the necessary components for their specific needs without creating redundant extension systems across different domains, thereby reducing tech-debt while maintaining comprehensive integration coverage.
Solution Approach 2:
The toolkit enables dynamic configuration of integration parameters such as connection types, data formats, authentication methods, and error handling strategies through parameterized integration patterns. This allows a single universal toolkit to adapt to various integration scenarios by changing parameters rather than requiring multiple hard-coded extension systems, reducing complexity while improving integration coverage.
3Adaptability or versatility
If extension systems are developed to integrate sensitive data protection technologies, then integration functionality is achieved, but implementation time is delayed
Solution Approach 1:
The integration toolkit includes pre-built connection patterns, pre-configured adapters, and pre-tested integration templates that are prepared in advance for common enterprise systems and scenarios. Enterprises can deploy these pre-actioned integration components immediately without undergoing lengthy development cycles, thereby achieving full integration functionality while significantly reducing implementation time compared to building extension systems from scratch.
Data Source
AI summary
The integration software toolkit has four core components: “Control Cube”, “Discovery”, “Qualifier”&“Resolution”. The “Control Cube” core component primary capabilities are to transmit functional instructions and serve as gateways to interact with backend and frontend system functions. The “Discovery” core component correct data stores sensitive data elements. The “Qualifier” core component retains real-time sensitive data compliance policies, which will be used to determine whether an offshore, nearshore or onshore production support engineer can or cannot see sensitive data at the database field-level. The “Resolution” Reactive-AI core component main capability is to perform sensitive data error resolutions with no human involvements if offshore or nearshore support engineers are denied access. The integration software toolkit can be implemented at any industry (i.e., healthcare, finance, banks, retail & airline), which are storing sensitive data for daily operations; and seamlessly configurable to align with their specific use cases and data compliance requirements.