Automated Data Dictionary Metadata for Marketplace Listings
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Solution Overview
Problem
Current data sharing methods are cumbersome, especially for smaller entities, as they are slow, expensive, and lack scalability, making it difficult for smaller businesses to access valuable large data sets due to high logistics and costs, and traditional methods introduce latency and delays in data access.
Innovation Solution
A data exchange system facilitated by cloud computing services allows data providers to share data without copying it, using a centralized hub for listing and controlling access, enabling secure, scalable, and timely data sharing through automated metadata generation and updates for data dictionaries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional data sharing methods are used, then data can be shared, but the process is slow and expensive with high logistics costs
Solution Approach 1:
The patent enables data sharing without physical copying by using a centralized data exchange hub that provides virtual access to data. Data consumers can query and access data through the hub without transferring actual data files, eliminating logistics costs associated with physical data transfer while maintaining fast access speeds.
Solution Approach 2:
The centralized data exchange hub acts as an intermediary between data providers and consumers. This hub manages data sharing operations, providing a efficient communication channel that eliminates direct point-to-point data transfers and reduces logistics overhead while maintaining high access speed.
2Speed
If traditional data sharing methods are used, then data can be shared, but latency and delays are introduced
Solution Approach 1:
The system pre-establishes a centralized data exchange hub with metadata catalogs and access protocols before actual data requests. This preliminary setup enables rapid data discovery and access without time-consuming on-demand configurations, reducing latency while maintaining fast data retrieval speeds.
Solution Approach 2:
The centralized hub provides universal access to multiple data sources through a single interface, eliminating the need for separate data sharing setups for each data provider. This multi-functional approach reduces operational delays and introduces minimal latency while maintaining high data access speed.
3Adaptability or versatility
If data is shared without copying, then scalability is improved, but control and security management becomes complex
Solution Approach 1:
The patent segments data access control into discrete metadata attributes and permission levels managed by the centralized hub. Each data resource has associated metadata that defines access rights, allowing scalable management of numerous data sources through standardized control segments rather than complex centralized management.
Solution Approach 2:
The system implements feedback mechanisms where data providers can monitor and manage access to their data through the hub, and the hub automatically enforces access control policies. This feedback loop simplifies security management by automating control decisions while maintaining scalability across multiple data sources.
Data Source
AI summary
A data dictionary generation system automatically populates and updates a data dictionary for listings offering shared data. A data dictionary includes metadata describing the shared data, including the individual objects, such as the individual tables, schemas, views, and functions. The shared data and each individual data object may be described in the data dictionary by a set of data fields that corresponds to the shared dataset or the object type of the individual object. The data dictionary can be presented to data consumers along with the description of the listing to provide data consumers with a comprehensive description of the shared data provided by a listing, including a high-level summary of the shared data and description of each individual object included in the shared data. The data dictionary allows data consumers to understand the contents of the shared data and how to use the shared data.