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CAMBRIDGE SEMANTICS
The only knowledge graph platform built on a high-performance, in-memory MPP semantic graph engine, capable of processing at in-memory speeds. Able to support large and complex models, ever-expanding data volumes, diverse data sources and types, complex TRAINING - CAMBRIDGE SEMANTICS Anzo 4.0 Bootcamp To coincide with our 4.0 product release, Cambridge Semantics is pleased to announce Anzo 4.0 Bootcamp Training. This training covers the core concepts of Anzo and focuses on the new innovative features of Anzo 4.0. Participants will learn how to ingest data from various sources and auto-generate ontologies, navigate the catalog of Anzo objects generated, and visualizeANZOGRAPH® DB
Horizontally Scalable Graph Database Built for Online Analytics and Data Harmonization Take on data harmonization and linked data challenges with AnzoGraph DB, a market-leading analytical graph database. AnzoGraph DB provides industrialized online performance for enterprise-scale graph applications. AnzoGraph DB uses familiar SPARQL*/OWL for semantic graphs but also supportsDATA FABRIC
The Data Fabric is an architecture for modern data management that anticipates the need to connect data across the enterprise at speed and scale. Knowledge graph is central to the success of any Data Fabric as an agile integration overlay that blends complex and diverse data into easy-to-consume data products for end-users, data scientists, and applications. Anzo enables the implementation ofANZO PLATFORM
The scaleable knowledge graph platform for data integration and analytics. Anzo makes turning siloed data into enterprise-scale knowledge graphs faster and easier than ever. From there, anything’s possible. Anzo is a complete knowledge graph platform built on a high-performance graph database engine, called AnzoGraph, that uses an in-memory MPP processing paradigm to execute queries against LEARN RDF - CAMBRIDGE SEMANTICSSEE MORE ON CAMBRIDGESEMANTICS.COM INTRODUCTION TO THE SEMANTIC WEBSEMANTIC UNIVERSITY
Our Vision Getting started with Semantic Web technologies seems much harder today than it should be. There is little material accessible to those new to the space, and almost none geared to a less technical audience that might be involved in funding semantic technology projects. The irony is that Semantic Web technologies should be easier for people to understand than other technologiesRDFS VS. OWL
RDFS vs. Owl We have introduced both RDFS and OWL as data modeling languages for describing RDF data. So which should you use? The quick answer is that although each has its place in the Semantic Web world, in general you should be using OWL. This article does a more thorough comparison of the two modeling languages. Prerequisites RDFS Introduction OWL 101 Today's Lesson RDFS allows you to ACCELERATE DATA SCIENCE WITH KNOWLEDGE GRAPHS Accelerating Data Science with Knowledge Graphs. "Do more with less". —Every executive to every line-of-business. Further emphasized by pandemic, this adage and circumstance has accelerated growth in data science automation. This white paper further expands on how knowledge graphs meet the needs of modern data science. Grab the White Paper.CAMBRIDGE SEMANTICS
The only knowledge graph platform built on a high-performance, in-memory MPP semantic graph engine, capable of processing at in-memory speeds. Able to support large and complex models, ever-expanding data volumes, diverse data sources and types, complex TRAINING - CAMBRIDGE SEMANTICS Anzo 4.0 Bootcamp To coincide with our 4.0 product release, Cambridge Semantics is pleased to announce Anzo 4.0 Bootcamp Training. This training covers the core concepts of Anzo and focuses on the new innovative features of Anzo 4.0. Participants will learn how to ingest data from various sources and auto-generate ontologies, navigate the catalog of Anzo objects generated, and visualizeANZOGRAPH® DB
Horizontally Scalable Graph Database Built for Online Analytics and Data Harmonization Take on data harmonization and linked data challenges with AnzoGraph DB, a market-leading analytical graph database. AnzoGraph DB provides industrialized online performance for enterprise-scale graph applications. AnzoGraph DB uses familiar SPARQL*/OWL for semantic graphs but also supportsDATA FABRIC
The Data Fabric is an architecture for modern data management that anticipates the need to connect data across the enterprise at speed and scale. Knowledge graph is central to the success of any Data Fabric as an agile integration overlay that blends complex and diverse data into easy-to-consume data products for end-users, data scientists, and applications. Anzo enables the implementation ofANZO PLATFORM
The scaleable knowledge graph platform for data integration and analytics. Anzo makes turning siloed data into enterprise-scale knowledge graphs faster and easier than ever. From there, anything’s possible. Anzo is a complete knowledge graph platform built on a high-performance graph database engine, called AnzoGraph, that uses an in-memory MPP processing paradigm to execute queries against LEARN RDF - CAMBRIDGE SEMANTICSSEE MORE ON CAMBRIDGESEMANTICS.COM INTRODUCTION TO THE SEMANTIC WEBSEMANTIC UNIVERSITY
Our Vision Getting started with Semantic Web technologies seems much harder today than it should be. There is little material accessible to those new to the space, and almost none geared to a less technical audience that might be involved in funding semantic technology projects. The irony is that Semantic Web technologies should be easier for people to understand than other technologiesRDFS VS. OWL
RDFS vs. Owl We have introduced both RDFS and OWL as data modeling languages for describing RDF data. So which should you use? The quick answer is that although each has its place in the Semantic Web world, in general you should be using OWL. This article does a more thorough comparison of the two modeling languages. Prerequisites RDFS Introduction OWL 101 Today's Lesson RDFS allows you to ACCELERATE DATA SCIENCE WITH KNOWLEDGE GRAPHS Accelerating Data Science with Knowledge Graphs. "Do more with less". —Every executive to every line-of-business. Further emphasized by pandemic, this adage and circumstance has accelerated growth in data science automation. This white paper further expands on how knowledge graphs meet the needs of modern data science. Grab the White Paper. TRAINING - CAMBRIDGE SEMANTICS Anzo 4.0 Bootcamp To coincide with our 4.0 product release, Cambridge Semantics is pleased to announce Anzo 4.0 Bootcamp Training. This training covers the core concepts of Anzo and focuses on the new innovative features of Anzo 4.0. Participants will learn how to ingest data from various sources and auto-generate ontologies, navigate the catalog of Anzo objects generated, and visualizeONTOLOGY MANAGEMENT
Ontology Management today has become a truly enterprise-scale problem. Here is the good news: The backbone of your enterprise ontologies already exists today - distributed across many data sources throughout your enterprise as well as within public ontologies. However, given the number of both internal and external sources of taxonomies and vocabularies addressing multiple domains, it is not INTRODUCTION TO THE SEMANTIC WEB Introduction to the Semantic Web. The Semantic Web, Web 3.0, the Linked Data Web, the Web of Datawhatever you call it, the Semantic Web represents the next major evolution in connecting information. It enables data to be linked from a source to any other source and to be understood by computers so that they can perform increasingly OWL 101 - CAMBRIDGE SEMANTICS OWL (or W eb O ntology L anguage) is the ontology (think “schema”) language of the Semantic Web. It is one of the core Semantic Web standards you must be familiar with, along with RDF and SPARQL. Its two primary uses are: This lesson gives a high level introduction to OWL and is suitable for beginners. A more detailed nuts & bolts lessonon
DATA CATALOGING
Secure, organize and govern all your data Anzo provides a newer, smarter approach to the data catalog by leveraging graph models encoding a Semantic Layer that describes the data in its business context, while capturing all types of disparate data, spanning all enterprise data sources and data sets. Regardless of whether data is to be sourced from applications, data warehouses or existing DOCUMENTATION CENTER Anzo 5.1 Getting Started Guide. Introduces Anzo concepts and user interface and gives guidance on basic setup and building a sample solution from scratch. HTML | PDF. Other Releases. Getting Started 5.0 Getting Started 4.4 Getting Started 4.3.RDFS VS. OWL
RDFS vs. Owl We have introduced both RDFS and OWL as data modeling languages for describing RDF data. So which should you use? The quick answer is that although each has its place in the Semantic Web world, in general you should be using OWL. This article does a more thorough comparison of the two modeling languages. Prerequisites RDFS Introduction OWL 101 Today's Lesson RDFS allows you to INTRODUCTION TO LINKED DATA Introduction The Semantic Web is a webby way to link data is one of the most brilliant definitions of the Semantic Web. Dave Beckett genially captured the very final essence, in one single sentence, of what we call Linked Data. If we look closer, we can find in it the main idea behind the Linked Data paradigm: using the Web model to publish and connect raw data. In today's lesson you'll learn SEMANTIC TECHNOLOGIES COMPARED The term semantic technologies represents a fairly diverse family of technologies that have been in existence for a long time and seek to help derive meaning from information. Some examples of semantic technologies include natural language processing (NLP), data mining, artificial intelligence (AI), category tagging, and semantic search. DATA FABRICS: THE KILLER USE CASE FOR KNOWLEDGE GRAPHS Today a good example of a new idea that has been around for awhile, but which is just now finding its killer use case is the use of knowledge graphs as part of a data fabric architecture. First defined in the 1970s, knowledge graphs are now part of our daily lives with digital platforms like Google, LinkedIn, and Facebook using them tocreate
CAMBRIDGE SEMANTICS
The only knowledge graph platform built on a high-performance, in-memory MPP semantic graph engine, capable of processing at in-memory speeds. Able to support large and complex models, ever-expanding data volumes, diverse data sources and types, complexANZOGRAPH® DB
Horizontally Scalable Graph Database Built for Online Analytics and Data Harmonization Take on data harmonization and linked data challenges with AnzoGraph DB, a market-leading analytical graph database. AnzoGraph DB provides industrialized online performance for enterprise-scale graph applications. AnzoGraph DB uses familiar SPARQL*/OWL for semantic graphs but also supportsANZO PLATFORM
The scaleable knowledge graph platform for data integration and analytics. Anzo makes turning siloed data into enterprise-scale knowledge graphs faster and easier than ever. From there, anything’s possible. Anzo is a complete knowledge graph platform built on a high-performance graph database engine, called AnzoGraph, that uses an in-memory MPP processing paradigm to execute queries againstDATA CATALOGING
Secure, organize and govern all your data Anzo provides a newer, smarter approach to the data catalog by leveraging graph models encoding a Semantic Layer that describes the data in its business context, while capturing all types of disparate data, spanning all enterprise data sources and data sets. Regardless of whether data is to be sourced from applications, data warehouses or existing DOCUMENTATION CENTER Anzo 5.1 Getting Started Guide. Introduces Anzo concepts and user interface and gives guidance on basic setup and building a sample solution from scratch. HTML | PDF. Other Releases. Getting Started 5.0 Getting Started 4.4 Getting Started 4.3.MODELING PATTERNS
Modeling is a very broad area and so is a rich source of patterns. Some patterns are very general while others are domain specific and may just be recommendations to use particular RDF vocabularies or terms. For this lesson we’ll focus on a couple of general patterns that provide a good starting point for those new to RDF modeling.RDF VS. XML
A person who cannot read braille cannot consume one of the two. The representation is what matters in the XML world. In this analogy, RDF represents the informational content of the book; XML is a choice of delivery mechanism (Braille or print). Both parts matter, for sure, but they are two different things. USING KNOWLEDGE GRAPHS & CONNECTED DATA TO DRIVE PATIENT Register for this live fireside chat featuring Jamie Powers, a Principal Consultant for Healthcare at Cambridge Semantics, and Judy Barkal, Chief Technology and Medical Informatics Officer at M2Gen, to learn how they are using knowledge graphs and connected data to drive patient-centric data analytics in oncology research. During this chat,we
DATA FABRICS: THE KILLER USE CASE FOR KNOWLEDGE GRAPHS Today a good example of a new idea that has been around for awhile, but which is just now finding its killer use case is the use of knowledge graphs as part of a data fabric architecture. First defined in the 1970s, knowledge graphs are now part of our daily lives with digital platforms like Google, LinkedIn, and Facebook using them tocreate
GEOSPATIAL KNOWLEDGE GRAPHS Use points, circles and polygons to partition spaces and maps Define Regions Understand distances, zones, things that overlap or touch andmore
CAMBRIDGE SEMANTICS
The only knowledge graph platform built on a high-performance, in-memory MPP semantic graph engine, capable of processing at in-memory speeds. Able to support large and complex models, ever-expanding data volumes, diverse data sources and types, complexANZOGRAPH® DB
Horizontally Scalable Graph Database Built for Online Analytics and Data Harmonization Take on data harmonization and linked data challenges with AnzoGraph DB, a market-leading analytical graph database. AnzoGraph DB provides industrialized online performance for enterprise-scale graph applications. AnzoGraph DB uses familiar SPARQL*/OWL for semantic graphs but also supportsANZO PLATFORM
The scaleable knowledge graph platform for data integration and analytics. Anzo makes turning siloed data into enterprise-scale knowledge graphs faster and easier than ever. From there, anything’s possible. Anzo is a complete knowledge graph platform built on a high-performance graph database engine, called AnzoGraph, that uses an in-memory MPP processing paradigm to execute queries againstDATA CATALOGING
Secure, organize and govern all your data Anzo provides a newer, smarter approach to the data catalog by leveraging graph models encoding a Semantic Layer that describes the data in its business context, while capturing all types of disparate data, spanning all enterprise data sources and data sets. Regardless of whether data is to be sourced from applications, data warehouses or existing DOCUMENTATION CENTER Anzo 5.1 Getting Started Guide. Introduces Anzo concepts and user interface and gives guidance on basic setup and building a sample solution from scratch. HTML | PDF. Other Releases. Getting Started 5.0 Getting Started 4.4 Getting Started 4.3.MODELING PATTERNS
Modeling is a very broad area and so is a rich source of patterns. Some patterns are very general while others are domain specific and may just be recommendations to use particular RDF vocabularies or terms. For this lesson we’ll focus on a couple of general patterns that provide a good starting point for those new to RDF modeling.RDF VS. XML
A person who cannot read braille cannot consume one of the two. The representation is what matters in the XML world. In this analogy, RDF represents the informational content of the book; XML is a choice of delivery mechanism (Braille or print). Both parts matter, for sure, but they are two different things. USING KNOWLEDGE GRAPHS & CONNECTED DATA TO DRIVE PATIENT Register for this live fireside chat featuring Jamie Powers, a Principal Consultant for Healthcare at Cambridge Semantics, and Judy Barkal, Chief Technology and Medical Informatics Officer at M2Gen, to learn how they are using knowledge graphs and connected data to drive patient-centric data analytics in oncology research. During this chat,we
DATA FABRICS: THE KILLER USE CASE FOR KNOWLEDGE GRAPHS Today a good example of a new idea that has been around for awhile, but which is just now finding its killer use case is the use of knowledge graphs as part of a data fabric architecture. First defined in the 1970s, knowledge graphs are now part of our daily lives with digital platforms like Google, LinkedIn, and Facebook using them tocreate
GEOSPATIAL KNOWLEDGE GRAPHS Use points, circles and polygons to partition spaces and maps Define Regions Understand distances, zones, things that overlap or touch andmore
ANZO PLATFORM
The scaleable knowledge graph platform for data integration and analytics. Anzo makes turning siloed data into enterprise-scale knowledge graphs faster and easier than ever. From there, anything’s possible. Anzo is a complete knowledge graph platform built on a high-performance graph database engine, called AnzoGraph, that uses an in-memory MPP processing paradigm to execute queries againstDATA FABRIC
The Data Fabric is an architecture for modern data management that anticipates the need to connect data across the enterprise at speed and scale. Knowledge graph is central to the success of any Data Fabric as an agile integration overlay that blends complex and diverse data into easy-to-consume data products for end-users, data scientists, and applications. Anzo enables the implementation of INTRODUCTION TO LINKED DATA Introduction The Semantic Web is a webby way to link data is one of the most brilliant definitions of the Semantic Web. Dave Beckett genially captured the very final essence, in one single sentence, of what we call Linked Data. If we look closer, we can find in it the main idea behind the Linked Data paradigm: using the Web model to publish and connect raw data. In today's lesson you'll learnDATA LAYERS
Data Scientists and Citizen Data Scientists alike can use Data Layers to infer, create and connect data through business rules, Machine Learning and other popular predictive or statistical analytics techniques as well as add remotely sourced data to the mix on-the-fly, so that the most up to the minute information necessary to complete an analysis through Federated Query Data Layer configuration. USING KNOWLEDGE GRAPHS & CONNECTED DATA TO DRIVE PATIENT Register for this live fireside chat featuring Jamie Powers, a Principal Consultant for Healthcare at Cambridge Semantics, and Judy Barkal, Chief Technology and Medical Informatics Officer at M2Gen, to learn how they are using knowledge graphs and connected data to drive patient-centric data analytics in oncology research. During this chat,we
NLP & THE SEMANTIC WEB NLP & the Semantic Web Natural language processing (NLP) and Semantic Web technologies are both Semantic Technologies, but with different and complementary roles in data management. In fact, the combination of NLP and Semantic Web technologies enables enterprises to combine structured and unstructured data in ways that are simply not practical using traditional tools. This lesson will ROBUST, AGILE, AND COMPREHENSIVE: THE STORY OF THE DATA This whitepaper explains what an Enterprise Data Fabric is, how it allows organizations to model and integrate data at whatever level of granularity desired and how Anzo's semantic technology adds a semantic layer of metadata that adds depth and meaning to the graph overall. DATA FABRICS: THE KILLER USE CASE FOR KNOWLEDGE GRAPHS Today a good example of a new idea that has been around for awhile, but which is just now finding its killer use case is the use of knowledge graphs as part of a data fabric architecture. First defined in the 1970s, knowledge graphs are now part of our daily lives with digital platforms like Google, LinkedIn, and Facebook using them tocreate
SEMANTIC LAYERS FOR ON-DEMAND DATA ACCESS Smart Data Lake platforms providing semantic layers are automating data access and data management for accelerated insight. These platforms, based on knowledge graphs, allow organizations on-demand access to all relevant data, internal or external, regardless of the source format or type (i.e. structured, unstructured orsemi-structured).
LIFE SCIENCES & HEALTHCARE: TWO INDUSTRIES SEPARATED BY Life Sciences (Pharmaceutical, Biotechnology and Medical Device) and Healthcare (Providers and Payors) organizations need to be able to handle and analyze many diverse sets of longitudinal health data in order to manage long-term and often complex patient health journeys and optimize outcomes. Complex and mission-critical data models forCAMBRIDGE SEMANTICS
The only knowledge graph platform built on a high-performance, in-memory MPP semantic graph engine, capable of processing at in-memory speeds. Able to support large and complex models, ever-expanding data volumes, diverse data sources and types, complexANZOGRAPH® DB
Horizontally Scalable Graph Database Built for Online Analytics and Data Harmonization Take on data harmonization and linked data challenges with AnzoGraph DB, a market-leading analytical graph database. AnzoGraph DB provides industrialized online performance for enterprise-scale graph applications. AnzoGraph DB uses familiar SPARQL*/OWL for semantic graphs but also supportsANZO PLATFORM
The scaleable knowledge graph platform for data integration and analytics. Anzo makes turning siloed data into enterprise-scale knowledge graphs faster and easier than ever. From there, anything’s possible. Anzo is a complete knowledge graph platform built on a high-performance graph database engine, called AnzoGraph, that uses an in-memory MPP processing paradigm to execute queries againstDATA CATALOGING
Secure, organize and govern all your data Anzo provides a newer, smarter approach to the data catalog by leveraging graph models encoding a Semantic Layer that describes the data in its business context, while capturing all types of disparate data, spanning all enterprise data sources and data sets. Regardless of whether data is to be sourced from applications, data warehouses or existing DOCUMENTATION CENTER Anzo 5.1 Getting Started Guide. Introduces Anzo concepts and user interface and gives guidance on basic setup and building a sample solution from scratch. HTML | PDF. Other Releases. Getting Started 5.0 Getting Started 4.4 Getting Started 4.3.MODELING PATTERNS
Modeling is a very broad area and so is a rich source of patterns. Some patterns are very general while others are domain specific and may just be recommendations to use particular RDF vocabularies or terms. For this lesson we’ll focus on a couple of general patterns that provide a good starting point for those new to RDF modeling.RDF VS. XML
A person who cannot read braille cannot consume one of the two. The representation is what matters in the XML world. In this analogy, RDF represents the informational content of the book; XML is a choice of delivery mechanism (Braille or print). Both parts matter, for sure, but they are two different things. USING KNOWLEDGE GRAPHS & CONNECTED DATA TO DRIVE PATIENT Register for this live fireside chat featuring Jamie Powers, a Principal Consultant for Healthcare at Cambridge Semantics, and Judy Barkal, Chief Technology and Medical Informatics Officer at M2Gen, to learn how they are using knowledge graphs and connected data to drive patient-centric data analytics in oncology research. During this chat,we
DATA FABRICS: THE KILLER USE CASE FOR KNOWLEDGE GRAPHS Today a good example of a new idea that has been around for awhile, but which is just now finding its killer use case is the use of knowledge graphs as part of a data fabric architecture. First defined in the 1970s, knowledge graphs are now part of our daily lives with digital platforms like Google, LinkedIn, and Facebook using them tocreate
GEOSPATIAL KNOWLEDGE GRAPHS Use points, circles and polygons to partition spaces and maps Define Regions Understand distances, zones, things that overlap or touch andmore
CAMBRIDGE SEMANTICS
The only knowledge graph platform built on a high-performance, in-memory MPP semantic graph engine, capable of processing at in-memory speeds. Able to support large and complex models, ever-expanding data volumes, diverse data sources and types, complexANZOGRAPH® DB
Horizontally Scalable Graph Database Built for Online Analytics and Data Harmonization Take on data harmonization and linked data challenges with AnzoGraph DB, a market-leading analytical graph database. AnzoGraph DB provides industrialized online performance for enterprise-scale graph applications. AnzoGraph DB uses familiar SPARQL*/OWL for semantic graphs but also supportsANZO PLATFORM
The scaleable knowledge graph platform for data integration and analytics. Anzo makes turning siloed data into enterprise-scale knowledge graphs faster and easier than ever. From there, anything’s possible. Anzo is a complete knowledge graph platform built on a high-performance graph database engine, called AnzoGraph, that uses an in-memory MPP processing paradigm to execute queries againstDATA CATALOGING
Secure, organize and govern all your data Anzo provides a newer, smarter approach to the data catalog by leveraging graph models encoding a Semantic Layer that describes the data in its business context, while capturing all types of disparate data, spanning all enterprise data sources and data sets. Regardless of whether data is to be sourced from applications, data warehouses or existing DOCUMENTATION CENTER Anzo 5.1 Getting Started Guide. Introduces Anzo concepts and user interface and gives guidance on basic setup and building a sample solution from scratch. HTML | PDF. Other Releases. Getting Started 5.0 Getting Started 4.4 Getting Started 4.3.MODELING PATTERNS
Modeling is a very broad area and so is a rich source of patterns. Some patterns are very general while others are domain specific and may just be recommendations to use particular RDF vocabularies or terms. For this lesson we’ll focus on a couple of general patterns that provide a good starting point for those new to RDF modeling.RDF VS. XML
A person who cannot read braille cannot consume one of the two. The representation is what matters in the XML world. In this analogy, RDF represents the informational content of the book; XML is a choice of delivery mechanism (Braille or print). Both parts matter, for sure, but they are two different things. USING KNOWLEDGE GRAPHS & CONNECTED DATA TO DRIVE PATIENT Register for this live fireside chat featuring Jamie Powers, a Principal Consultant for Healthcare at Cambridge Semantics, and Judy Barkal, Chief Technology and Medical Informatics Officer at M2Gen, to learn how they are using knowledge graphs and connected data to drive patient-centric data analytics in oncology research. During this chat,we
DATA FABRICS: THE KILLER USE CASE FOR KNOWLEDGE GRAPHS Today a good example of a new idea that has been around for awhile, but which is just now finding its killer use case is the use of knowledge graphs as part of a data fabric architecture. First defined in the 1970s, knowledge graphs are now part of our daily lives with digital platforms like Google, LinkedIn, and Facebook using them tocreate
GEOSPATIAL KNOWLEDGE GRAPHS Use points, circles and polygons to partition spaces and maps Define Regions Understand distances, zones, things that overlap or touch andmore
ANZO PLATFORM
The scaleable knowledge graph platform for data integration and analytics. Anzo makes turning siloed data into enterprise-scale knowledge graphs faster and easier than ever. From there, anything’s possible. Anzo is a complete knowledge graph platform built on a high-performance graph database engine, called AnzoGraph, that uses an in-memory MPP processing paradigm to execute queries againstDATA FABRIC
The Data Fabric is an architecture for modern data management that anticipates the need to connect data across the enterprise at speed and scale. Knowledge graph is central to the success of any Data Fabric as an agile integration overlay that blends complex and diverse data into easy-to-consume data products for end-users, data scientists, and applications. Anzo enables the implementation of INTRODUCTION TO LINKED DATA Introduction The Semantic Web is a webby way to link data is one of the most brilliant definitions of the Semantic Web. Dave Beckett genially captured the very final essence, in one single sentence, of what we call Linked Data. If we look closer, we can find in it the main idea behind the Linked Data paradigm: using the Web model to publish and connect raw data. In today's lesson you'll learnDATA LAYERS
Data Scientists and Citizen Data Scientists alike can use Data Layers to infer, create and connect data through business rules, Machine Learning and other popular predictive or statistical analytics techniques as well as add remotely sourced data to the mix on-the-fly, so that the most up to the minute information necessary to complete an analysis through Federated Query Data Layer configuration. USING KNOWLEDGE GRAPHS & CONNECTED DATA TO DRIVE PATIENT Register for this live fireside chat featuring Jamie Powers, a Principal Consultant for Healthcare at Cambridge Semantics, and Judy Barkal, Chief Technology and Medical Informatics Officer at M2Gen, to learn how they are using knowledge graphs and connected data to drive patient-centric data analytics in oncology research. During this chat,we
NLP & THE SEMANTIC WEB NLP & the Semantic Web Natural language processing (NLP) and Semantic Web technologies are both Semantic Technologies, but with different and complementary roles in data management. In fact, the combination of NLP and Semantic Web technologies enables enterprises to combine structured and unstructured data in ways that are simply not practical using traditional tools. This lesson will ROBUST, AGILE, AND COMPREHENSIVE: THE STORY OF THE DATA This whitepaper explains what an Enterprise Data Fabric is, how it allows organizations to model and integrate data at whatever level of granularity desired and how Anzo's semantic technology adds a semantic layer of metadata that adds depth and meaning to the graph overall. DATA FABRICS: THE KILLER USE CASE FOR KNOWLEDGE GRAPHS Today a good example of a new idea that has been around for awhile, but which is just now finding its killer use case is the use of knowledge graphs as part of a data fabric architecture. First defined in the 1970s, knowledge graphs are now part of our daily lives with digital platforms like Google, LinkedIn, and Facebook using them tocreate
SEMANTIC LAYERS FOR ON-DEMAND DATA ACCESS Smart Data Lake platforms providing semantic layers are automating data access and data management for accelerated insight. These platforms, based on knowledge graphs, allow organizations on-demand access to all relevant data, internal or external, regardless of the source format or type (i.e. structured, unstructured orsemi-structured).
LIFE SCIENCES & HEALTHCARE: TWO INDUSTRIES SEPARATED BY Life Sciences (Pharmaceutical, Biotechnology and Medical Device) and Healthcare (Providers and Payors) organizations need to be able to handle and analyze many diverse sets of longitudinal health data in order to manage long-term and often complex patient health journeys and optimize outcomes. Complex and mission-critical data models forCAMBRIDGE SEMANTICS
The only knowledge graph platform built on a high-performance, in-memory MPP semantic graph engine, capable of processing at in-memory speeds. Able to support large and complex models, ever-expanding data volumes, diverse data sources and types, complexDATA FABRIC
The Data Fabric is an architecture for modern data management that anticipates the need to connect data across the enterprise at speed and scale. Knowledge graph is central to the success of any Data Fabric as an agile integration overlay that blends complex and diverse data into easy-to-consume data products for end-users, data scientists, and applications. Anzo enables the implementation of LEARN RDF - CAMBRIDGE SEMANTICSSEE MORE ON CAMBRIDGESEMANTICS.COMDATA CATALOGING
Secure, organize and govern all your data Anzo provides a newer, smarter approach to the data catalog by leveraging graph models encoding a Semantic Layer that describes the data in its business context, while capturing all types of disparate data, spanning all enterprise data sources and data sets. Regardless of whether data is to be sourced from applications, data warehouses or existing INTRODUCTION TO LINKED DATA Introduction The Semantic Web is a webby way to link data is one of the most brilliant definitions of the Semantic Web. Dave Beckett genially captured the very final essence, in one single sentence, of what we call Linked Data. If we look closer, we can find in it the main idea behind the Linked Data paradigm: using the Web model to publish and connect raw data. In today's lesson you'll learnDATA LAYERS
Data Scientists and Citizen Data Scientists alike can use Data Layers to infer, create and connect data through business rules, Machine Learning and other popular predictive or statistical analytics techniques as well as add remotely sourced data to the mix on-the-fly, so that the most up to the minute information necessary to complete an analysis through Federated Query Data Layer configuration. DOCUMENTATION CENTER Anzo 5.1 Getting Started Guide. Introduces Anzo concepts and user interface and gives guidance on basic setup and building a sample solution from scratch. HTML | PDF. Other Releases. Getting Started 5.0 Getting Started 4.4 Getting Started 4.3. THE RISE OF THE KNOWLEDGE GRAPH The Rise of the Knowledge Graph. This practical report details combining graph data and knowledge representation into a knowledge graph. Authors Sean Martin, Ben Szekely, and Dean Allemang take you through all necessary steps to plan and design your knowledge graphfuture.
GEOSPATIAL KNOWLEDGE GRAPHS Use points, circles and polygons to partition spaces and maps Define Regions Understand distances, zones, things that overlap or touch andmore
SEMANTIC LAYERS FOR ON-DEMAND DATA ACCESS Smart Data Lake platforms providing semantic layers are automating data access and data management for accelerated insight. These platforms, based on knowledge graphs, allow organizations on-demand access to all relevant data, internal or external, regardless of the source format or type (i.e. structured, unstructured orsemi-structured).
CAMBRIDGE SEMANTICS
The only knowledge graph platform built on a high-performance, in-memory MPP semantic graph engine, capable of processing at in-memory speeds. Able to support large and complex models, ever-expanding data volumes, diverse data sources and types, complexDATA FABRIC
The Data Fabric is an architecture for modern data management that anticipates the need to connect data across the enterprise at speed and scale. Knowledge graph is central to the success of any Data Fabric as an agile integration overlay that blends complex and diverse data into easy-to-consume data products for end-users, data scientists, and applications. Anzo enables the implementation of LEARN RDF - CAMBRIDGE SEMANTICSSEE MORE ON CAMBRIDGESEMANTICS.COMDATA CATALOGING
Secure, organize and govern all your data Anzo provides a newer, smarter approach to the data catalog by leveraging graph models encoding a Semantic Layer that describes the data in its business context, while capturing all types of disparate data, spanning all enterprise data sources and data sets. Regardless of whether data is to be sourced from applications, data warehouses or existing INTRODUCTION TO LINKED DATA Introduction The Semantic Web is a webby way to link data is one of the most brilliant definitions of the Semantic Web. Dave Beckett genially captured the very final essence, in one single sentence, of what we call Linked Data. If we look closer, we can find in it the main idea behind the Linked Data paradigm: using the Web model to publish and connect raw data. In today's lesson you'll learnDATA LAYERS
Data Scientists and Citizen Data Scientists alike can use Data Layers to infer, create and connect data through business rules, Machine Learning and other popular predictive or statistical analytics techniques as well as add remotely sourced data to the mix on-the-fly, so that the most up to the minute information necessary to complete an analysis through Federated Query Data Layer configuration. DOCUMENTATION CENTER Anzo 5.1 Getting Started Guide. Introduces Anzo concepts and user interface and gives guidance on basic setup and building a sample solution from scratch. HTML | PDF. Other Releases. Getting Started 5.0 Getting Started 4.4 Getting Started 4.3. THE RISE OF THE KNOWLEDGE GRAPH The Rise of the Knowledge Graph. This practical report details combining graph data and knowledge representation into a knowledge graph. Authors Sean Martin, Ben Szekely, and Dean Allemang take you through all necessary steps to plan and design your knowledge graphfuture.
GEOSPATIAL KNOWLEDGE GRAPHS Use points, circles and polygons to partition spaces and maps Define Regions Understand distances, zones, things that overlap or touch andmore
SEMANTIC LAYERS FOR ON-DEMAND DATA ACCESS Smart Data Lake platforms providing semantic layers are automating data access and data management for accelerated insight. These platforms, based on knowledge graphs, allow organizations on-demand access to all relevant data, internal or external, regardless of the source format or type (i.e. structured, unstructured orsemi-structured).
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Horizontally Scalable Graph Database Built for Online Analytics and Data Harmonization Take on data harmonization and linked data challenges with AnzoGraph DB, a market-leading analytical graph database. AnzoGraph DB provides industrialized online performance for enterprise-scale graph applications. AnzoGraph DB uses familiar SPARQL*/OWL for semantic graphs but also supportsANZO PLATFORM
The scaleable knowledge graph platform for data integration and analytics. Anzo makes turning siloed data into enterprise-scale knowledge graphs faster and easier than ever. From there, anything’s possible. Anzo is a complete knowledge graph platform built on a high-performance graph database engine, called AnzoGraph, that uses an in-memory MPP processing paradigm to execute queries againstDATA LAYERS
Data Scientists and Citizen Data Scientists alike can use Data Layers to infer, create and connect data through business rules, Machine Learning and other popular predictive or statistical analytics techniques as well as add remotely sourced data to the mix on-the-fly, so that the most up to the minute information necessary to complete an analysis through Federated Query Data Layer configuration.ONTOLOGY MANAGEMENT
Ontology Management today has become a truly enterprise-scale problem. Here is the good news: The backbone of your enterprise ontologies already exists today - distributed across many data sources throughout your enterprise as well as within public ontologies. However, given the number of both internal and external sources of taxonomies and vocabularies addressing multiple domains, it is notANZO SOLUTIONS
Anzo delivers value quickly for its customers, often through practical solutions in related business functions. The semantic data models applied in each solution naturally connect to form an enterprise data fabric, addressing real business problems and building transformational value as each new solution joins the data fabric. As a true future-proof data fabric platform, Anzo excels where dataRDF VS. XML
A person who cannot read braille cannot consume one of the two. The representation is what matters in the XML world. In this analogy, RDF represents the informational content of the book; XML is a choice of delivery mechanism (Braille or print). Both parts matter, for sure, but they are two different things.SEMANTIC UNIVERSITY
Our Vision Getting started with Semantic Web technologies seems much harder today than it should be. There is little material accessible to those new to the space, and almost none geared to a less technical audience that might be involved in funding semantic technology projects. The irony is that Semantic Web technologies should be easier for people to understand than other technologies DATA FABRICS: THE KILLER USE CASE FOR KNOWLEDGE GRAPHS Today a good example of a new idea that has been around for awhile, but which is just now finding its killer use case is the use of knowledge graphs as part of a data fabric architecture. First defined in the 1970s, knowledge graphs are now part of our daily lives with digital platforms like Google, LinkedIn, and Facebook using them tocreate
'DATA, DATA EVERYWHERE....' Data is the new oil. It is the fuel that is enabling companies to improve the customer experience, enhance workforce productivity, increase operational efficiency, and adapt to competitor threats. It has also become a new source of revenue, as companies discover ways to productize their data or take advantage of it for delivering newproducts
WHAT IS A GRAPH DATABASE? 2018 has been touted as "The Year of the Graph", as more and more o rganizations both large and small have recently begun to invest in graph database technology as they look to draw insights and meaning from existing data resources to streamline their operations. But what exactly is a graph database, and how exactly does it provide meaningful insights into the relationships between your data? This website stores cookies on your computer. These cookies are used to collect information about how you interact with our website and allow us to remember you. We use this information in order to improve and customize your browsing experience and for analytics and metrics about our visitors both on this website and other media. To find out more about the cookies we use, see our Privacy Policy.
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