Enterprise Data Element Review via Selective Metadata Collection
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Solution Overview
Problem
Current enterprise-level data element review systems face inefficiencies in collecting and managing metadata and access permissions across a multiplicity of data elements, particularly in identifying modified elements and handling collection failures, leading to resource wastage and prolonged processing times.
Innovation Solution
The system employs a data access event collection subsystem to identify modified data elements, a data element dancer to selectively collect metadata and permissions for a subset of elements based on a script, and a data element crawler to efficiently gather metadata and permissions for all elements, with a failure monitoring subsystem ensuring continuous operation by switching to crawling in case of collection failures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If the system collects metadata and access permissions for all data elements, then the completeness of data element information is improved, but the resource utilization and processing time increase significantly
Solution Approach 1:
The patent extracts and identifies only the modified data elements from the complete set using a metadata modification subassembly, rather than processing all data elements. This selective extraction approach maintains information completeness for relevant elements while reducing overall processing scope and time
Solution Approach 2:
The system performs preliminary identification of modified data elements through event collection and metadata comparison before the actual metadata collection phase. This preliminary action filters the target set, enabling subsequent efficient collection only from identified modified elements rather than all elements
2Productivity
If the system selectively collects metadata only from accessed elements, then the resource utilization and processing time are reduced, but the risk of missing modified elements increases
Solution Approach 1:
The patent implements a feedback mechanism where the metadata modification subassembly continuously monitors and compares metadata states, using event collection results to identify modified elements. This feedback loop ensures accurate identification of modified elements while enabling selective collection, maintaining both efficiency and reliability
Solution Approach 2:
The system performs preliminary identification of modified data elements through event collection and metadata comparison before the actual metadata collection phase. This preliminary action filters the target set, enabling subsequent efficient collection only from identified modified elements rather than all elements
3Loss of information
If the system uses a crawler to collect metadata from all data elements, then the completeness of data collection is improved, but the resource consumption increases
Solution Approach 1:
The patent extracts and identifies only the modified data elements from the complete set using a metadata modification subassembly, rather than processing all data elements. This selective extraction approach maintains information completeness for relevant elements while reducing overall processing scope and resource consumption
Solution Approach 2:
The system performs partial action by collecting metadata only from the identified subset of modified data elements rather than all elements. This partial action is sufficient to meet the requirement of tracking modifications while consuming fewer resources than complete collection
4Measurement precision
If the system monitors data access events continuously, then the detection of modified elements is improved, but the complexity of the monitoring subsystem increases
Solution Approach 1:
The patent segments the monitoring function into distinct modular components: an event collection subsystem that gathers access events, and a metadata modification subassembly that processes events and identifies modified elements. This segmentation improves detection accuracy through specialized functions while managing complexity through modular design
Data Source
AI summary
An enterprise level data element review system including a data access event collection subsystem operative to collect data access event notifications relating to ones of a multiplicity of data elements, a data element metadata modification subassembly receiving an output from the data access event collection subsystem and providing a script indicating which data elements have had a metadata modification over a given period of time, and a data element dancer operative to collect at least one of metadata and access permissions for a plurality of data elements which is substantially less than the multiplicity of data elements and is selected on the basis of the script.