Press release
Knowledge Graph Market Size,Share,Growth,Competition,Trends,Growth Opportunities and Forecast (2024-2031)
E-commerce, content delivery and social media platforms use knowledge graphs to power recommendation systems that enhance user experiences and drive user engagement. Many organizations need effective solutions to integrate and make sense of the vast amounts of structured and unstructured data they generate. Knowledge graphs are employed to enrich content by linking related information and providing context.Knowledge graphs improve the efficiency and accuracy of search engines and discovery platforms, enabling users to find relevant information more easily. As data privacy regulations become more stringent organizations seek data governance solutions. Knowledge graphs assist in data governance by providing data lineage and visibility into data usage.Download Free PDF Sample -https://www.datamintelligence.com/download-sample/knowledge-graph-market
Market Dynamics
Internet of Things(IoT) devices produce a wide variety of data. Knowledge Graphs enable the integration of data from diverse IoT sources, providing a holistic view of the IoT ecosystem. IoT data come in different formats and standards. Knowledge graphs help establish semantic interoperability, ensuring that data from various IoT devices can be understood and analyzed coherently. Knowledge graphs process and analyze this data in real time, allowing for immediate decision-making and response to IoT events and anomalies. IoT data becomes more valuable when placed in context. Knowledge Graphs provide the context by linking IoT data to relevant entities and relationships, enabling deeper insights. Knowledge graphs, when combined with IoT data, support predictive analytics. The is particularly valuable for applications like predictive maintenance, where IoT sensors help anticipate equipment failures. IoT devices in logistics and supply chain management benefit from knowledge graphs. The graphs provide real-time visibility and optimization opportunities throughout the supply chain.
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Segment Analysis
Based on the data source, the knowledge graph market is divided into structured, unstructured and semi-structured. The structured segment accounted for 1/3rd of the market share in the global knowledge graph market. Structured data sources provide well-organized and standardized data and make it easier to integrate information from multiple sources. The integration is crucial for building comprehensive and interconnected knowledge graphs.
Structured data sources offer higher data quality compared to unstructured or semi-structured data. The is essential for ensuring that the information in the knowledge graph is accurate and trustworthy. Structured data sources are semantically consistent, with clear definitions and standardized formats. The consistency facilitates the creation of meaningful relationships and connections within the knowledge graph. In many domains and industries, structured data sources adhere to industry-specific standards and regulations, ensuring compliance and data consistency in the knowledge graph.
Competitive Landscape
The major global players in the market include AWS, Cambridge Semantics, Franz Inc., Google, IBM Corporation, Microsoft, Stardog, Neo4j, Ontotext and Oracle.
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