Data Marketplace Virtual Interface for Big Data Retrieval
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Solution Overview
Problem
Users face challenges in identifying and retrieving relevant data items from large, complex datasets due to their non-human readable nature and the inefficiencies of traditional search techniques, which are not suited for data structures like tables and databases.
Innovation Solution
A data marketplace system with a unified, virtualized interface allows users to search, request, and retrieve data assets across different systems, utilizing natural language searches, machine learning for recommendations, and a centralized catalog for data storage and retrieval, enabling efficient access to relevant data assets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional searching techniques are used to search for data items, then the search process can be performed, but the search effectiveness is poor because data structures like tables and databases do not have human readable qualities that web pages have
Solution Approach 1:
The patent introduces a specialized search intermediary layer that sits between traditional search techniques and data assets. This intermediary includes search bots that crawl data catalogs, extract metadata, and create searchable indexes. The system mediates between user search queries and the underlying data structures by translating natural language queries into data-specific search criteria, thereby improving search effectiveness without requiring users to directly interact with complex data formats.
Solution Approach 2:
The patent replaces traditional mechanical search methods (keyword matching on visible text) with intelligent systems that understand data semantics. Machine learning models analyze data metadata, schemas, and content to generate meaningful search results. The system substitutes simple text-based retrieval with sophisticated algorithms that can interpret data relationships, constraints, and relevance, thereby overcoming the limitation of non-human-readable data structures.
2Adaptability or versatility
If users manually search through multiple databases to find relevant data items, then comprehensive data can be accessed, but the time required to identify and retrieve data items increases significantly
Solution Approach 1:
The patent implements preliminary action by pre-processing and indexing data from multiple databases before users need to search. Search bots continuously crawl data catalogs, extract metadata, and organize data assets in advance. When users submit search queries, the system can immediately retrieve pre-processed results rather than scanning raw databases in real-time. This preliminary preparation significantly reduces data retrieval time while maintaining comprehensive data accessibility.
Solution Approach 2:
The patent merges multiple distributed databases into a unified virtual data marketplace. Instead of requiring users to manually search through separate database systems, the system combines data assets from multiple sources into a single searchable interface. The virtual marketplace aggregates metadata and data descriptions from various databases, allowing users to access comprehensive data across multiple systems through one search operation, thereby reducing retrieval time while maintaining data versatility.
3Ease of operation
If traditional search engines are applied to data assets, then searching can be performed, but the search results are not optimized for data structures because data can be very large, be comprised simply of numbers or other data fields, and may not have human readable qualities
Solution Approach 1:
The patent applies local quality by creating specialized search handling for different data types and structures. Instead of using a single generic search algorithm, the system implements data-type-specific search strategies. For example, numerical data receives different search treatment than text-based metadata, and structured data schemas receive specialized querying capabilities. This localized approach to search processing improves both usability and accuracy by matching search methods to data characteristics.
Solution Approach 2:
The patent changes search parameters dynamically based on data asset properties. The system adjusts search thresholds, matching criteria, and result ranking algorithms according to the specific characteristics of the data being searched. For large datasets, the system may adjust pagination and filtering parameters; for numerical data, it may apply statistical thresholds; for structured data, it may modify schema-matching parameters. These parameter changes enable accurate and usable search results across diverse data formats.
Data Source
AI summary
A method, system, and computer readable storage to implement a data marketplace which stored data assets, such as tables, models, variables, etc. All of the data assets (assets) can be searched and retrieved from the data marketplace notwithstanding that the assets can be stored at different locations, in different forms, and in different platforms through an entire big data system. The data marketplace also predicts and suggests assets which will be likely to be relevant to a user's current project.