This book is a guide to designing and building knowledge graphs from enterprise relational databases in practice.\ It presents a principled framework centered on mapping patterns to connect relational databases with knowledge graphs, the roles within an organization responsible for the knowledge graph, and the process that combines data and people. The content of this book is applicable to knowledge graphs being built either with property graph or RDF graph technologies. Knowledge graphs are fulfilling the vision of creating intelligent systems that integrate knowledge and data at large scale. Tech giants have adopted knowledge graphs for the foundation of next-generation enterprise data and metadata management, search, recommendation, analytics, intelligent agents, and more. We are now observing an increasing number of enterprises that seek to adopt knowledge graphs to develop a competitive edge. In order for enterprises to design and build knowledge graphs, they need to understand the critical data stored in relational databases. How can enterprises successfully adopt knowledge graphs to integrate data and knowledge, without boiling the ocean? This book provides the answers.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Juan Sequeda is the Principal Scientist at data.world. He joined through the acquisition of Capsenta, a company he founded as a spin-off from his research. Juan’s goal is to reliably create knowledge from inscrutable data. His academic and industry work has been on designing and building knowledge graphs for enterprise data integration where he has researched and developed technologies for semantic and graph data virtualization, ontology and graph data modeling and schema mapping, and data integration methodologies. Juan serves as a bridge between academia and industry through standardization committees, like serving as the co-chair of the Property Graph Schema Working Group and a past member of the Graph Query Languages task force of the Linked Data Benchmark Council (LDBC), as well as a past invited expert member and standards editor at the World Wide Web Consortium (W3C). Juan holds a Ph.D. in Computer Science from The University of Texas at Austin. He is the recipient of the NSF Graduate Research Fellowship, 2nd place in the 2013 Semantic Web Challenge for his work on ConstituteProject.org, Best Student Research Paper at International Semantic Web Conference 2014, and the 2015 Best Transfer and Innovation Project awarded by the Institute for Applied Informatics.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
EUR 2,25 per la spedizione in U.S.A.
Destinazione, tempi e costiEUR 4,78 per la spedizione da Regno Unito a U.S.A.
Destinazione, tempi e costiDa: PBShop.store UK, Fairford, GLOS, Regno Unito
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000. Codice articolo GB-9783031007880
Quantità: 1 disponibili
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: New. Codice articolo 44571019-n
Quantità: Più di 20 disponibili
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: As New. Unread book in perfect condition. Codice articolo 44571019
Quantità: Più di 20 disponibili
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
Condizione: New. Codice articolo ABLING22Oct2817100391496
Quantità: Più di 20 disponibili
Da: Best Price, Torrance, CA, U.S.A.
Condizione: New. SUPER FAST SHIPPING. Codice articolo 9783031007880
Quantità: 2 disponibili
Da: California Books, Miami, FL, U.S.A.
Condizione: New. Codice articolo I-9783031007880
Quantità: Più di 20 disponibili
Da: GreatBookPricesUK, Woodford Green, Regno Unito
Condizione: New. Codice articolo 44571019-n
Quantità: Più di 20 disponibili
Da: Grand Eagle Retail, Mason, OH, U.S.A.
Paperback. Condizione: new. Paperback. This book is a guide to designing and building knowledge graphs from enterprise relational databases in practice.\ It presents a principled framework centered on mapping patterns to connect relational databases with knowledge graphs, the roles within an organization responsible for the knowledge graph, and the process that combines data and people. The content of this book is applicable to knowledge graphs being built either with property graph or RDF graph technologies. Knowledge graphs are fulfilling the vision of creating intelligent systems that integrate knowledge and data at large scale. Tech giants have adopted knowledge graphs for the foundation of next-generation enterprise data and metadata management, search, recommendation, analytics, intelligent agents, and more. We are now observing an increasing number of enterprises that seek to adopt knowledge graphs to develop a competitive edge. In order for enterprises to design and build knowledge graphs, they need to understand the critical data stored in relational databases. How can enterprises successfully adopt knowledge graphs to integrate data and knowledge, without boiling the ocean? This book provides the answers. This book is a guide to designing and building knowledge graphs from enterprise relational databases in practice.\ It presents a principled framework centered on mapping patterns to connect relational databases with knowledge graphs, the roles within an organization responsible for the knowledge graph, and the process that combines data and people. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9783031007880
Quantità: 1 disponibili
Da: Ria Christie Collections, Uxbridge, Regno Unito
Condizione: New. In English. Codice articolo ria9783031007880_new
Quantità: Più di 20 disponibili
Da: Rarewaves.com USA, London, LONDO, Regno Unito
Paperback. Condizione: New. This book is a guide to designing and building knowledge graphs from enterprise relational databases in practice.\ It presents a principled framework centered on mapping patterns to connect relational databases with knowledge graphs, the roles within an organization responsible for the knowledge graph, and the process that combines data and people. The content of this book is applicable to knowledge graphs being built either with property graph or RDF graph technologies. Knowledge graphs are fulfilling the vision of creating intelligent systems that integrate knowledge and data at large scale. Tech giants have adopted knowledge graphs for the foundation of next-generation enterprise data and metadata management, search, recommendation, analytics, intelligent agents, and more. We are now observing an increasing number of enterprises that seek to adopt knowledge graphs to develop a competitive edge. In order for enterprises to design and build knowledge graphs, they need to understand the critical data stored in relational databases. How can enterprises successfully adopt knowledge graphs to integrate data and knowledge, without boiling the ocean? This book provides the answers. Codice articolo LU-9783031007880
Quantità: 1 disponibili