According to Gartner’s Top 10 Data and Analytics Trends for 2021, knowledge graphs are the foundation of modern data and analytics, with capabilities to enhance and improve user collaboration ...

The real-world knowledge graph starts with the foundational first-party data generated by the city's infrastructure, IoT assets, networks, and operational processes. However, such data may not ...

Knowledge graph technology is transforming the way that organizations manage and make sense of data: A Unified View: By integrating data from multiple sources, knowledge graphs eliminate data ...

#4 Data Migration. One of the most powerful applications for semantic Knowledge Graphs is data migration. Populating a data lake, consolidating mortgage systems or on-boarding new data feeds are all ...

For example, Google's Knowledge Graph lets users obtain comprehensive information about entities on the search results page. Recommendation Systems: ... real-time data analysis, ...

The flexibility offered by a knowledge-graph-powered data catalog enables near-immediate support for new types of data sources; a knowledge graph makes it easy to extend the model to represent ...

Knowledge graphs: The link between data and meaning While Google popularized the term “knowledge graph” in 2012, the concept of representing knowledge as interconnected information has roots ...

Knowledge graphs are a valuable tool that organizations can use to manage the vast amounts of data they collect, store, and analyze. At Data Summit 2023, Joseph Hilger, COO, Enterprise Knowledge LLC ...

The semantic technologies underpinning RDF knowledge graphs are primed for data mesh and data fabric architectures — and their synthesis. They’re certainly ideal for crafting data products.

LinkedIn, for example, uses a knowledge graph to structure and interconnect data about its members, jobs, titles, and other entities. It uses its knowledge graph to enhance its recommendation ...