Metadata-Driven Dataset Classification for Cross-Environment Compliance
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Solution Overview
Problem
Existing data governance systems require manual updates of datasets across different environments to comply with changing regulations, leading to inefficiencies and compliance challenges.
Innovation Solution
A system with a classification management device that automatically applies classification codes to datasets based on metadata and policy repositories, ensuring compliance across various data environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual updates of datasets are performed to comply with changing regulations, then regulatory compliance can be achieved, but efficiency decreases and time consumption increases
Solution Approach 1:
The system enables self-service automation where the classification management device automatically queries metadata repositories, retrieves classification codes, and applies them to datasets without requiring manual intervention from actors within the organization. This transforms the manual compliance process into an autonomous system that self-manages regulatory adherence.
Solution Approach 2:
Classification codes are pre-stored in the policy repository along with metadata about data attributes and classification requirements. When a dataset needs compliance checking, the system queries pre-existing metadata and applies pre-prepared classification codes, eliminating the need for manual retrieval and application of regulatory rules.
2Reliability
If manual updates of code are performed in each data environment, then data governance policies can be enforced, but device complexity and operational burden increase
Solution Approach 1:
The classification management device serves multiple functions across different data environments: it queries metadata from repositories, retrieves classification codes, and applies them to datasets. This single multi-functional device replaces the need for separate manual processes in each data environment, reducing operational complexity while maintaining comprehensive policy enforcement.
Solution Approach 2:
The classification management device acts as an intermediary between data environments and regulatory requirements. Instead of manually updating code in each data environment, the intermediary system automatically queries metadata, retrieves appropriate classification codes, and applies them, simplifying the overall operational architecture.
3Productivity
If automated classification code application is implemented, then productivity and efficiency improve, but system complexity increases
Solution Approach 1:
The system segments functionality into distinct components: a classification management device for automation, a metadata repository for storing data attribute information, and a policy repository for storing classification codes. This segmentation allows each component to perform its specific function independently, making the overall complex automated system more manageable and maintainable.
Data Source
AI summary
Systems and methods for providing automated data governance are disclosed. The system may include a plurality of data environments, a metadata repository storing data attributes and classification requirements, a policy repository, one or more processors, and a memory in communication with the one or more processors storing instructions to execute steps of a method. The system may receive a first dataset from a first data environment having a first dataset ID. The system may transmit the dataset ID to the metadata repository and the metadata repository may return an indication that the first dataset includes at least one data attribute and at least one associated classification requirement. The system may transmit the classification requirement to the policy repository and receive classification code associated with the classification requirement. The system may modify the first dataset by transmitting instructions to the first data environment to execute the classification code.