Data Inventory System for Managing Personal Data Flows
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Solution Overview
Problem
Organizations face challenges in identifying and managing data flows within complex data networks, particularly in implementing effective data controls for personal data, due to the numerous components and processing activities involved, which can lead to difficulties in recognizing appropriate data controls and minimizing data breaches.
Innovation Solution
A data model generation and population system that identifies and represents data assets and processing activities within a data network, using attributes to map relationships and generate a graphical user interface for visualizing data flows, thereby facilitating the implementation of proper data controls.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If organizations implement comprehensive data controls across all components and processing activities in complex data networks, then data security and compliance improve, but system complexity and implementation difficulty increase significantly
Solution Approach 1:
The patent segments the complex data network into discrete data assets, each with specific attributes and data flows. By dividing the network into manageable components (data assets, data flows, processing activities), the system enables targeted control implementation without overwhelming complexity. Each segment can be analyzed and controlled independently while contributing to overall security.
Solution Approach 2:
The patent introduces an intermediary data inventory system that mediates between the complex data network and control mechanisms. This inventory serves as a structured representation layer that simplifies the analysis and control of data flows, acting as a bridge between the raw complexity of the network and the need for systematic security controls.
2Reliability
If organizations manually identify and map all data flows through complex data networks, then complete data control coverage is achieved, but time consumption and resource requirements increase significantly
Solution Approach 1:
The patent enables the data network system to self-analyze and self-map its data flows through automated analysis of data assets and their attributes. The system automatically identifies data flows, relationships, and control requirements without requiring extensive manual intervention, thereby achieving comprehensive coverage while minimizing time and resource investment.
Solution Approach 2:
The patent performs preliminary analysis and mapping of data assets and flows before implementing controls. By pre-identifying data assets, their attributes, and flow relationships, the system prepares the groundwork for control implementation, reducing the time needed for actual control deployment and ensuring complete coverage from the outset.
3Measurement precision
If organizations create detailed inventories and visual representations of all data assets and flows, then data flow identification accuracy improves, but data processing and storage requirements increase
Solution Approach 1:
The patent applies local quality by creating detailed attribute representations only for specific data assets and their immediate data flows, rather than uniformly documenting every aspect of the entire network. This targeted approach maintains high identification accuracy for critical data elements while minimizing overall data processing and storage requirements by focusing detail where most needed.
Data Source
AI summary
In particular embodiments, a data processing data inventory generation system is configured to: (1) generate a data model (e.g., a data inventory) for one or more data assets utilized by a particular organization; (2) generate a respective data inventory for each of the one or more data assets; and (3) map one or more relationships between one or more aspects of the data inventory, the one or more data assets, etc. within the data model. In particular embodiments, a data asset (e.g., data system, software application, etc.) may include, for example, any entity that collects, processes, contains, and/or transfers personal data (e.g., such as a software application, “internet of things” computerized device, database, website, data-center, server, etc.). For example, a first data asset may include any software or device (e.g., server or servers) utilized by a particular entity for such data collection, processing, transfer, storage, etc.