Knowledge Graph Enterprise Data Semantics
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Solution Overview
Problem
Business enterprises face challenges in obtaining timely and relevant data analytics, as traditional reporting methods often take several months to produce reports that may be outdated by the time they are received, failing to meet users' specific information needs.
Innovation Solution
A system comprising a knowledge base, search input engine, and query engine that builds a knowledge graph by integrating enterprise data with publicly accessible data and analytics, allowing users to pose queries and access relevant data without relying on IT groups, using a knowledge graph to represent data semantics and context.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional reporting methods are used to produce specialized reports, then comprehensive data analysis can be achieved, but the turnaround time becomes excessively long (three to six months)
Solution Approach 1:
The system segments enterprise data into structured knowledge graphs with entities, relationships, and attributes, allowing parallel processing and querying of specific data aspects rather than waiting for comprehensive report generation
Solution Approach 2:
The system performs preliminary data integration and knowledge graph construction continuously in the background, so when users need data, the infrastructure is already prepared and queries can execute immediately without months-long processing
2Quantity of substance
If traditional IT group reporting is used, then data can be aggregated and presented, but the data becomes outdated by the time reports are delivered
Solution Approach 1:
The knowledge graph is dynamically updated and maintained in real-time, allowing users to query current data states whenever needed rather than receiving static historical snapshots from periodic reports
Solution Approach 2:
Users can directly query the knowledge graph themselves without relying on IT groups to generate reports, enabling them to retrieve relevant data on-demand when they need it
3Adaptability or versatility
If specialized reports are requested from IT groups, then specific information needs can be addressed, but the process requires extensive coordination and delays user productivity
Solution Approach 1:
The system empowers users to directly query the knowledge graph using natural language or structured queries, eliminating the need to request reports through IT groups and enabling immediate data access for their workflows
Solution Approach 2:
The knowledge graph serves multiple functions simultaneously - it stores enterprise data, enables ad-hoc querying, supports analytical operations, and provides real-time access, replacing multiple specialized reporting processes with a single universal system
Data Source
AI summary
A knowledge base provides a mechanism for storing an organization's data in a way that represents the semantics of the data being stored. The knowledge base may include a knowledge graph that represents relationships between the different classes of data comprising the organization's data. Data that is loaded into the knowledge graph may be stored in data tables associated with the knowledge graph, and cross referenced with node identifiers that contain the data. Searching the knowledge base includes parsing a search input to identify terms in the search input, and mapping the terms to nodes in the knowledge base using the cross referenced information. The relationships among the identified nodes are used to identify a suitable application for processing the search.