Metastore Manager for Cross-Platform Metadata Synchronization
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Solution Overview
Problem
Establishing dependencies between different data management platforms for cross-platform data management is challenging and can result in data loss and corruption due to differing structures and configurations.
Innovation Solution
Implementing a metastore manager that facilitates access to data and metadata across multiple data management platforms, enabling cross-platform data operations and utilizing AI/ML systems with user consent and privacy safeguards.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data management platforms operate independently with different structures and configurations, then each platform maintains its own data integrity and autonomy, but establishing dependencies between platforms becomes challenging and can result in data loss and corruption
Solution Approach 1:
The patent introduces a metastore manager as an intermediary component that mediates between different data management platforms. This manager handles metadata exchange and dependency tracking across platforms, enabling cross-platform data operations without requiring the platforms themselves to directly understand each other's structures. The metastore manager translates and adapts metadata formats, preventing data loss and corruption while maintaining platform autonomy.
2Reliability
If a metastore manager is implemented to facilitate cross-platform data access, then data exchange between platforms is enabled and data loss is reduced, but the system complexity increases with additional metadata management components
Solution Approach 1:
The metastore manager is designed as a universal component that can interface with multiple different data management platforms simultaneously. It provides multi-functional capabilities including metadata storage, dependency tracking, access control, and data translation. By consolidating these functions into a single manager, the patent reduces the need for separate complex integration components for each platform pair.
Solution Approach 2:
The patent segments metadata management into distinct functional components within the metastore manager, such as separate modules for dependency tracking, access control, and data translation. This segmentation allows each component to be optimized independently and simplifies the overall system architecture by dividing complex tasks into manageable units.
3Productivity
If AI/ML systems are utilized for data processing across platforms, then data processing capabilities are enhanced, but user privacy and control over AI/ML usage must be ensured
Solution Approach 1:
The patent implements feedback mechanisms that allow users to control and monitor AI/ML processing activities. The system provides users with visibility into what data is being processed, by whom, and for what purposes. Users can receive notifications, adjust their privacy settings, and control data sharing preferences in real-time, creating a feedback loop that empowers users to manage their privacy while benefiting from enhanced processing capabilities.
Data Source
AI summary
A metastore manager facilitates access to data/metadata stored on at least one data management platform. A first data processing operation is initiated, in association with a data set maintained in a first data store associated with a first data management platform, to generate a first processed data set. The first processed data set is stored in the first data store and a first metadata set corresponding to the first processed data set is stored in a first metastore associated with the first data store. The first metadata set includes partition metadata indicative of partitioning information associated with the first processed data set. A synchronization operation is implemented to store, in a second metastore associated with a second data management platform, a second metadata set corresponding to a subset of the first metadata set. The metastore manager may facilitate access, by a data processing pipeline, to the processed data set.