Learn what a knowledge graph is and how it plays a salient role in enterprises and how to apply knowledge graphs for various business use cases across the data spectrum – from management to analytics and machine learning.
Introduction to Knowledge Graphs for Information Architects.pdfHeather Hedden
There is a growing interest in knowledge graphs to organize information and make it findable in organizations with large amounts of data and content. Unlike other data technologies, a knowledge graph has a structure that is typically based on a taxonomy and ontology, and thus should involve information architects. Knowledge graphs also have more benefits than information findability, including discovery, analysis, and recommendation. Knowledge graphs bring together content and data.
An enterprise knowledge graph involves a change in thinking about information and its access. Instead of designing information architecture in individual applications, an intranet, or website, a knowledge graph extracts data and links to content that exists in multiple different applications and repositories, linking them in a web or graph-like structure by means of customized, semantic relationships.
The document provides an introduction to knowledge graphs. It discusses how knowledge graphs are being used by large enterprises and intelligent agents to capture concepts, entities, and relationships within domains to drive business, generate insights, and enhance relationships. The presentation will cover an overview of what knowledge graphs are, who uses them, why they are used, and how to use them. It then provides some examples of how knowledge graphs are applied, including in intelligent agents, semantic web, search engines, social networks, biology, enterprise knowledge management, and more.
This workshop presentation from Enterprise Knowledge team members Joe Hilger, Founder and COO, and Sara Nash, Technical Analyst, was delivered on June 8, 2020 as part of the Data Summit 2020 virtual conference. The 3-hour workshop provided an interdisciplinary group of participants with a definition of what a knowledge graph is, how it is implemented, and how it can be used to increase the value of your organization’s datas. This slide deck gives an overview of the KM concepts that are necessary for the implementation of knowledge graphs as a foundation for Enterprise Artificial Intelligence (AI). Hilger and Nash also outlined four use cases for knowledge graphs, including recommendation engines and natural language query on structured data.
This document discusses how graphs and Neo4j can be used for various use cases in banking. It provides an agenda for the discussion including introductions to graphs and Neo4j, banking data overviews, and specific use cases like fraud detection, risk analysis, knowledge graphs, and customer 360 views. Examples are given for how graph databases could help with each use case, with a fraud detection demo. Additional potential uses include identity and access management and regulatory compliance.
Property graph vs. RDF Triplestore comparison in 2020Ontotext
This presentation goes all the way from intro "what graph databases are" to table comparing the RDF vs. PG plus two different diagrams presenting the market circa 2020
This document discusses knowledge graphs and how they can be used to drive intelligence into data. It describes how knowledge graphs can organize different types of data relationships and enable applications such as semantic search, pattern matching, and analyzing dependencies. Specific use cases are provided for skills discovery, root cause analysis, and military equipment management. Knowledge graphs are presented as a way to bridge data silos and enable a unified data fabric.
Architecting Agile Data Applications for ScaleDatabricks
Data analytics and reporting platforms historically have been rigid, monolithic, hard to change and have limited ability to scale up or scale down. I can’t tell you how many times I have heard a business user ask for something as simple as an additional column in a report and IT says it will take 6 months to add that column because it doesn’t exist in the datawarehouse. As a former DBA, I can tell you the countless hours I have spent “tuning” SQL queries to hit pre-established SLAs. This talk will talk about how to architect modern data and analytics platforms in the cloud to support agility and scalability. We will include topics like end to end data pipeline flow, data mesh and data catalogs, live data and streaming, performing advanced analytics, applying agile software development practices like CI/CD and testability to data applications and finally taking advantage of the cloud for infinite scalability both up and down.
Knowledge Graphs & Graph Data Science, More Context, Better Predictions - Neo...Neo4j
The document discusses how knowledge graphs and graph data science can provide more context and enable better predictions. It provides examples of using knowledge graphs for interactive browsing of patent and pathway data, cross-species ontology graph queries, identifying relevant COVID-19 genes using graph algorithms, and sub-phenotyping patient populations using graph embeddings. The key message is that knowledge graphs harness relationships to provide deep, dynamic context for analytics and machine learning.
Introduction to Knowledge Graphs for Information Architects.pdfHeather Hedden
There is a growing interest in knowledge graphs to organize information and make it findable in organizations with large amounts of data and content. Unlike other data technologies, a knowledge graph has a structure that is typically based on a taxonomy and ontology, and thus should involve information architects. Knowledge graphs also have more benefits than information findability, including discovery, analysis, and recommendation. Knowledge graphs bring together content and data.
An enterprise knowledge graph involves a change in thinking about information and its access. Instead of designing information architecture in individual applications, an intranet, or website, a knowledge graph extracts data and links to content that exists in multiple different applications and repositories, linking them in a web or graph-like structure by means of customized, semantic relationships.
The document provides an introduction to knowledge graphs. It discusses how knowledge graphs are being used by large enterprises and intelligent agents to capture concepts, entities, and relationships within domains to drive business, generate insights, and enhance relationships. The presentation will cover an overview of what knowledge graphs are, who uses them, why they are used, and how to use them. It then provides some examples of how knowledge graphs are applied, including in intelligent agents, semantic web, search engines, social networks, biology, enterprise knowledge management, and more.
This workshop presentation from Enterprise Knowledge team members Joe Hilger, Founder and COO, and Sara Nash, Technical Analyst, was delivered on June 8, 2020 as part of the Data Summit 2020 virtual conference. The 3-hour workshop provided an interdisciplinary group of participants with a definition of what a knowledge graph is, how it is implemented, and how it can be used to increase the value of your organization’s datas. This slide deck gives an overview of the KM concepts that are necessary for the implementation of knowledge graphs as a foundation for Enterprise Artificial Intelligence (AI). Hilger and Nash also outlined four use cases for knowledge graphs, including recommendation engines and natural language query on structured data.
This document discusses how graphs and Neo4j can be used for various use cases in banking. It provides an agenda for the discussion including introductions to graphs and Neo4j, banking data overviews, and specific use cases like fraud detection, risk analysis, knowledge graphs, and customer 360 views. Examples are given for how graph databases could help with each use case, with a fraud detection demo. Additional potential uses include identity and access management and regulatory compliance.
Property graph vs. RDF Triplestore comparison in 2020Ontotext
This presentation goes all the way from intro "what graph databases are" to table comparing the RDF vs. PG plus two different diagrams presenting the market circa 2020
This document discusses knowledge graphs and how they can be used to drive intelligence into data. It describes how knowledge graphs can organize different types of data relationships and enable applications such as semantic search, pattern matching, and analyzing dependencies. Specific use cases are provided for skills discovery, root cause analysis, and military equipment management. Knowledge graphs are presented as a way to bridge data silos and enable a unified data fabric.
Architecting Agile Data Applications for ScaleDatabricks
Data analytics and reporting platforms historically have been rigid, monolithic, hard to change and have limited ability to scale up or scale down. I can’t tell you how many times I have heard a business user ask for something as simple as an additional column in a report and IT says it will take 6 months to add that column because it doesn’t exist in the datawarehouse. As a former DBA, I can tell you the countless hours I have spent “tuning” SQL queries to hit pre-established SLAs. This talk will talk about how to architect modern data and analytics platforms in the cloud to support agility and scalability. We will include topics like end to end data pipeline flow, data mesh and data catalogs, live data and streaming, performing advanced analytics, applying agile software development practices like CI/CD and testability to data applications and finally taking advantage of the cloud for infinite scalability both up and down.
Knowledge Graphs & Graph Data Science, More Context, Better Predictions - Neo...Neo4j
The document discusses how knowledge graphs and graph data science can provide more context and enable better predictions. It provides examples of using knowledge graphs for interactive browsing of patent and pathway data, cross-species ontology graph queries, identifying relevant COVID-19 genes using graph algorithms, and sub-phenotyping patient populations using graph embeddings. The key message is that knowledge graphs harness relationships to provide deep, dynamic context for analytics and machine learning.
Presentation of the Semantic Knowledge Graph research paper at the 2016 IEEE 3rd International Conference on Data Science and Advanced Analytics (Montreal, Canada - October 18th, 2016)
Abstract—This paper describes a new kind of knowledge representation and mining system which we are calling the Semantic Knowledge Graph. At its heart, the Semantic Knowledge Graph leverages an inverted index, along with a complementary uninverted index, to represent nodes (terms) and edges (the documents within intersecting postings lists for multiple terms/nodes). This provides a layer of indirection between each pair of nodes and their corresponding edge, enabling edges to materialize dynamically from underlying corpus statistics. As a result, any combination of nodes can have edges to any other nodes materialize and be scored to reveal latent relationships between the nodes. This provides numerous benefits: the knowledge graph can be built automatically from a real-world corpus of data, new nodes - along with their combined edges - can be instantly materialized from any arbitrary combination of preexisting nodes (using set operations), and a full model of the semantic relationships between all entities within a domain can be represented and dynamically traversed using a highly compact representation of the graph. Such a system has widespread applications in areas as diverse as knowledge modeling and reasoning, natural language processing, anomaly detection, data cleansing, semantic search, analytics, data classification, root cause analysis, and recommendations systems. The main contribution of this paper is the introduction of a novel system - the Semantic Knowledge Graph - which is able to dynamically discover and score interesting relationships between any arbitrary combination of entities (words, phrases, or extracted concepts) through dynamically materializing nodes and edges from a compact graphical representation built automatically from a corpus of data representative of a knowledge domain.
Climbing the Ontology Mountain to Achieve a Successful Knowledge GraphEnterprise Knowledge
Tatiana Baquero Cakici, Senior KM Consultant, and Jennifer Doughty, Senior Solution Consultant from Enterprise Knowledge’s Data and Information Management (DIME) Division presented at the Taxonomy Boot Camp (KMWorld 2022) on November 17, 2022. KMWorld is the world’s leading knowledge management event that takes place every year in Washington, DC.
Their presentation “Climbing the Ontology Mountain to Achieve a Successful Knowledge Graph” focused on how ontologies have gained momentum as a strong foundation for resolving business challenges through semantic search solutions, recommendation engines, and AI strategies. Cakici and Doughty explained that taxonomists are now faced with the challenge of gaining knowledge and experience in designing and documenting complex solutions that involve the integration of taxonomies, ontologies, and knowledge graphs. They also emphasized that taxonomists are well poised to learn how to design user-centric ontologies, analyze and map data from various systems, and understand the technological architecture of knowledge graph solutions. After describing the key roles and responsibilities needed for a team to successfully implement Knowledge Graph projects, Cakici and Doughty shared practical ontology design considerations and best practices based on their own experience. Lastly, Cakici and Doughty reviewed the most common use cases for knowledge graphs and presented real world applications through a case study that illustrated ontology design and the value of knowledge graphs.
The document provides an overview of knowledge graphs and introduces metaphactory, a knowledge graph platform. It discusses what knowledge graphs are, examples like Wikidata, and standards like RDF. It also outlines an agenda for a hands-on session on loading sample data into metaphactory and exploring a knowledge graph.
GPT and Graph Data Science to power your Knowledge GraphNeo4j
In this workshop at Data Innovation Summit 2023, we demonstrated how you could learn from the network structure of a Knowledge Graph and use OpenAI’s GPT engine to populate and enhance your Knowledge Graph.
Key takeaways:
1. How Knowledge Graphs grow organically
2. How to deploy Graph Algorithms to learn from the topology of a graph
3. Integrate a Knowledge Graph with OpenAI’s GPT
4. Use Graph Node embeddings to feed Machine Learning workflow
Linked Data and Knowledge Graphs -- Constructing and Understanding Knowledge ...Jeff Z. Pan
Tutorial on "Linked Data and Knowledge Graphs -- Constructing and Understanding Knowledge Graphs" presented at the 4th Joint International Conference on Semantic Technologies (JIST2014)
This document provides a training guide for Databricks partners. It outlines Databricks' partner enablement program, which includes self-paced and instructor-led training courses to help partners make the most of their partnership. The courses cover topics like the Databricks platform, data engineering, machine learning, and industry solutions. Partners can earn badges by completing courses. The guide also discusses partner certification programs, champions programs for top technical experts, and sales training to prepare partners' customer-facing roles.
Choosing the Right Graph Database to Succeed in Your ProjectOntotext
The document discusses choosing the right graph database for projects. It describes Ontotext, a provider of graph database and semantic technology products. It outlines use cases for graph databases in areas like knowledge graphs, content management, and recommendations. The document then examines Ontotext's GraphDB semantic graph database product and how it can address key use cases. It provides guidance on choosing a GraphDB option based on project stage from learning to production.
Neo4j Generative AI workshop at GraphSummit London 14 Nov 2023.pdfNeo4j
The document outlines an agenda for a generative AI workshop covering topics such as building a knowledge graph from a GDB dataset, semantic search using vector indexes and graph patterns, generating node embeddings, and developing a marketing campaign application that integrates all the techniques discussed.
The perfect couple: Uniting Large Language Models and Knowledge Graphs for En...Neo4j
Large Language models are amazing but are also black-box models that often fail to capture and accurately represent factual knowledge. Knowledge graphs, by contrast, are structural knowledge models that explicitly represent knowledge and, indeed, allow us to detect implicit relationships. In this talk we will demonstrate how LLMs can be improved by Knowledge Graphs, and how LLM’s can augment Knowledge Graphs. A perfect couple!
Deep dive into LangChain integration with Neo4j.pptxTomazBratanic1
Deep dive into LangChain integrations with Neo4j. Learn how to query your graph with LangChain either by generating Cypher statements using LLMs or using the vector index.
The document provides an overview of knowledge graphs and the metaphactory knowledge graph platform. It defines knowledge graphs as semantic descriptions of entities and relationships using formal knowledge representation languages like RDF, RDFS and OWL. It discusses how knowledge graphs can power intelligent applications and gives examples like Google Knowledge Graph, Wikidata, and knowledge graphs in cultural heritage and life sciences. It also provides an introduction to key standards like SKOS, SPARQL, and Linked Data principles. Finally, it describes the main features and architecture of the metaphactory platform for creating and utilizing enterprise knowledge graphs.
This is Part 4 of the GoldenGate series on Data Mesh - a series of webinars helping customers understand how to move off of old-fashioned monolithic data integration architecture and get ready for more agile, cost-effective, event-driven solutions. The Data Mesh is a kind of Data Fabric that emphasizes business-led data products running on event-driven streaming architectures, serverless, and microservices based platforms. These emerging solutions are essential for enterprises that run data-driven services on multi-cloud, multi-vendor ecosystems.
Join this session to get a fresh look at Data Mesh; we'll start with core architecture principles (vendor agnostic) and transition into detailed examples of how Oracle's GoldenGate platform is providing capabilities today. We will discuss essential technical characteristics of a Data Mesh solution, and the benefits that business owners can expect by moving IT in this direction. For more background on Data Mesh, Part 1, 2, and 3 are on the GoldenGate YouTube channel: https://www.youtube.com/playlist?list=PLbqmhpwYrlZJ-583p3KQGDAd6038i1ywe
Webinar Speaker: Jeff Pollock, VP Product (https://www.linkedin.com/in/jtpollock/)
Mr. Pollock is an expert technology leader for data platforms, big data, data integration and governance. Jeff has been CTO at California startups and a senior exec at Fortune 100 tech vendors. He is currently Oracle VP of Products and Cloud Services for Data Replication, Streaming Data and Database Migrations. While at IBM, he was head of all Information Integration, Replication and Governance products, and previously Jeff was an independent architect for US Defense Department, VP of Technology at Cerebra and CTO of Modulant – he has been engineering artificial intelligence based data platforms since 2001. As a business consultant, Mr. Pollock was a Head Architect at Ernst & Young’s Center for Technology Enablement. Jeff is also the author of “Semantic Web for Dummies” and "Adaptive Information,” a frequent keynote at industry conferences, author for books and industry journals, formerly a contributing member of W3C and OASIS, and an engineering instructor with UC Berkeley’s Extension for object-oriented systems, software development process and enterprise architecture.
Data Catalog as the Platform for Data IntelligenceAlation
Data catalogs are in wide use today across hundreds of enterprises as a means to help data scientists and business analysts find and collaboratively analyze data. Over the past several years, customers have increasingly used data catalogs in applications beyond their search & discovery roots, addressing new use cases such as data governance, cloud data migration, and digital transformation. In this session, the founder and CEO of Alation will discuss the evolution of the data catalog, the many ways in which data catalogs are being used today, the importance of machine learning in data catalogs, and discuss the future of the data catalog as a platform for a broad range of data intelligence solutions.
The document discusses knowledge graphs and their value for organizations. It notes that two-thirds of Neo4j customers have implemented knowledge graphs and that 88% of CXOs believe knowledge graphs will significantly improve business outcomes. Knowledge graphs are described as interconnected datasets enriched with meaning to enable complex decision-making. Examples of how knowledge graphs have helped companies with recommendations, fraud detection, and track and trace are provided.
Data Architecture Strategies: The Rise of the Graph DatabaseDATAVERSITY
Graph databases are growing in popularity, with their ability to quickly discover and integrate key relationship between enterprise data sets. Business use cases such as recommendation engines, master data management, social networks, enterprise knowledge graphs and more provide valuable ways to leverage graph databases in your organization. This webinar provides an overview of graph database technologies, and how they can be used for practical applications to drive business value.
The State of Digital Transformation 2018 - 2019 by Brian SolisBrian Solis
"Digital is an enterprise-wide strategic priority — but there's work to be done," according to Brian Solis and Altimeter, a Prophet company.
Now in its fifth year, our annual “State of Digital Transformation” research continues to document the constantly evolving enterprise. As disruptive technologies and their impact on organizations and markets continue to progress, our research aims to capture the shifts and trends that are shaping modern digital transformation.
In 2019, strategic digital transformation is only becoming more pervasive moving beyond IT to impact competitiveness throughout the organization. Budgets are soaring. The list of disruptive technologies on the radar of stakeholders is expanding. Ownership is moving to the C-Suite and managed by cross-functional, collaborative groups. Customer experience (CX) continues to lead digital transformation investments, but as we observed in 2017, employee experience and organizational culture are also rising in importance to empower and accelerate change, growth, and innovation.
Digital Transformation as an Enterprise-Wide Movement
This year, it’s clear that digital transformation is maturing into an enterprise-wide movement. Digital transformation is modernizing how companies work and compete and helping them effectively adapt and grow in an evolving digital economy.
What’s also evident is that there is still much work to do as companies are, by and large, prioritizing technology over grasping the disruptive trends that are influencing markets and, more specifically, customer and employee behaviors and expectations.
Learn more here: https://insights.prophet.com/the-state-of-digital-transformation-2018-2019
The Future of Data Science and Machine Learning at Scale: A Look at MLflow, D...Databricks
Many had dubbed 2020 as the decade of data. This is indeed an era of data zeitgeist.
From code-centric software development 1.0, we are entering software development 2.0, a data-centric and data-driven approach, where data plays a central theme in our everyday lives.
As the volume and variety of data garnered from myriad data sources continue to grow at an astronomical scale and as cloud computing offers cheap computing and data storage resources at scale, the data platforms have to match in their abilities to process, analyze, and visualize at scale and speed and with ease — this involves data paradigm shifts in processing and storing and in providing programming frameworks to developers to access and work with these data platforms.
In this talk, we will survey some emerging technologies that address the challenges of data at scale, how these tools help data scientists and machine learning developers with their data tasks, why they scale, and how they facilitate the future data scientists to start quickly.
In particular, we will examine in detail two open-source tools MLflow (for machine learning life cycle development) and Delta Lake (for reliable storage for structured and unstructured data).
Other emerging tools such as Koalas help data scientists to do exploratory data analysis at scale in a language and framework they are familiar with as well as emerging data + AI trends in 2021.
You will understand the challenges of machine learning model development at scale, why you need reliable and scalable storage, and what other open source tools are at your disposal to do data science and machine learning at scale.
Databricks CEO Ali Ghodsi introduces Databricks Delta, a new data management system that combines the scale and cost-efficiency of a data lake, the performance and reliability of a data warehouse, and the low latency of streaming.
Data-Centric Business Transformation Using Knowledge GraphsAlan Morrison
From a talk at the Data Architecture Summit in Chicago in 2018--reviews digital transformation and what deep transformation really implies at the data layer. Cross-enterprise knowledge graphs are becoming feasible and can be a key enabler of deep transformation.
Collibra Data Citizen '19 - Bridging Data Privacy with Data Governance BigID Inc
This presentation was shown at the 2019 Collibra Data Citizen Event in New York City.
Presented by Nimrod Vax, Chief Product Officer & Co-Founder & Joaquin Sufuentes, Lead Architect, Metadata Managment and Personal Infomation Protection, enterprise Data Managment, Intel IT
Driving Talent Change for the Digital EnterprisePluralsight
This document discusses how IT roles and skills will need to change by 2020 to support digital transformation. It notes that traditional IT mindsets focused on processes, risk avoidance, and working in silos will need to shift to more adaptive, collaborative mindsets. The skills most in demand include relationship building, learning agility, creativity, and business acumen. IT staff will need more versatile technical skills and experience across different areas. Teams will also need to integrate IT and business staff to work more fluidly across functions. To develop these skills, companies should offer experience-based career paths, foster openness to change, and invest in competency development beyond traditional training.
DXC Technology https://www.dxc.technology DXC technology is the world’s leading independent, end-to-end IT services company. They lead digital transformations for clients by modernizing and integrating their mainstream IT, and by deploying digital solutions at scale to produce better business outcomes.
Presentation of the Semantic Knowledge Graph research paper at the 2016 IEEE 3rd International Conference on Data Science and Advanced Analytics (Montreal, Canada - October 18th, 2016)
Abstract—This paper describes a new kind of knowledge representation and mining system which we are calling the Semantic Knowledge Graph. At its heart, the Semantic Knowledge Graph leverages an inverted index, along with a complementary uninverted index, to represent nodes (terms) and edges (the documents within intersecting postings lists for multiple terms/nodes). This provides a layer of indirection between each pair of nodes and their corresponding edge, enabling edges to materialize dynamically from underlying corpus statistics. As a result, any combination of nodes can have edges to any other nodes materialize and be scored to reveal latent relationships between the nodes. This provides numerous benefits: the knowledge graph can be built automatically from a real-world corpus of data, new nodes - along with their combined edges - can be instantly materialized from any arbitrary combination of preexisting nodes (using set operations), and a full model of the semantic relationships between all entities within a domain can be represented and dynamically traversed using a highly compact representation of the graph. Such a system has widespread applications in areas as diverse as knowledge modeling and reasoning, natural language processing, anomaly detection, data cleansing, semantic search, analytics, data classification, root cause analysis, and recommendations systems. The main contribution of this paper is the introduction of a novel system - the Semantic Knowledge Graph - which is able to dynamically discover and score interesting relationships between any arbitrary combination of entities (words, phrases, or extracted concepts) through dynamically materializing nodes and edges from a compact graphical representation built automatically from a corpus of data representative of a knowledge domain.
Climbing the Ontology Mountain to Achieve a Successful Knowledge GraphEnterprise Knowledge
Tatiana Baquero Cakici, Senior KM Consultant, and Jennifer Doughty, Senior Solution Consultant from Enterprise Knowledge’s Data and Information Management (DIME) Division presented at the Taxonomy Boot Camp (KMWorld 2022) on November 17, 2022. KMWorld is the world’s leading knowledge management event that takes place every year in Washington, DC.
Their presentation “Climbing the Ontology Mountain to Achieve a Successful Knowledge Graph” focused on how ontologies have gained momentum as a strong foundation for resolving business challenges through semantic search solutions, recommendation engines, and AI strategies. Cakici and Doughty explained that taxonomists are now faced with the challenge of gaining knowledge and experience in designing and documenting complex solutions that involve the integration of taxonomies, ontologies, and knowledge graphs. They also emphasized that taxonomists are well poised to learn how to design user-centric ontologies, analyze and map data from various systems, and understand the technological architecture of knowledge graph solutions. After describing the key roles and responsibilities needed for a team to successfully implement Knowledge Graph projects, Cakici and Doughty shared practical ontology design considerations and best practices based on their own experience. Lastly, Cakici and Doughty reviewed the most common use cases for knowledge graphs and presented real world applications through a case study that illustrated ontology design and the value of knowledge graphs.
The document provides an overview of knowledge graphs and introduces metaphactory, a knowledge graph platform. It discusses what knowledge graphs are, examples like Wikidata, and standards like RDF. It also outlines an agenda for a hands-on session on loading sample data into metaphactory and exploring a knowledge graph.
GPT and Graph Data Science to power your Knowledge GraphNeo4j
In this workshop at Data Innovation Summit 2023, we demonstrated how you could learn from the network structure of a Knowledge Graph and use OpenAI’s GPT engine to populate and enhance your Knowledge Graph.
Key takeaways:
1. How Knowledge Graphs grow organically
2. How to deploy Graph Algorithms to learn from the topology of a graph
3. Integrate a Knowledge Graph with OpenAI’s GPT
4. Use Graph Node embeddings to feed Machine Learning workflow
Linked Data and Knowledge Graphs -- Constructing and Understanding Knowledge ...Jeff Z. Pan
Tutorial on "Linked Data and Knowledge Graphs -- Constructing and Understanding Knowledge Graphs" presented at the 4th Joint International Conference on Semantic Technologies (JIST2014)
This document provides a training guide for Databricks partners. It outlines Databricks' partner enablement program, which includes self-paced and instructor-led training courses to help partners make the most of their partnership. The courses cover topics like the Databricks platform, data engineering, machine learning, and industry solutions. Partners can earn badges by completing courses. The guide also discusses partner certification programs, champions programs for top technical experts, and sales training to prepare partners' customer-facing roles.
Choosing the Right Graph Database to Succeed in Your ProjectOntotext
The document discusses choosing the right graph database for projects. It describes Ontotext, a provider of graph database and semantic technology products. It outlines use cases for graph databases in areas like knowledge graphs, content management, and recommendations. The document then examines Ontotext's GraphDB semantic graph database product and how it can address key use cases. It provides guidance on choosing a GraphDB option based on project stage from learning to production.
Neo4j Generative AI workshop at GraphSummit London 14 Nov 2023.pdfNeo4j
The document outlines an agenda for a generative AI workshop covering topics such as building a knowledge graph from a GDB dataset, semantic search using vector indexes and graph patterns, generating node embeddings, and developing a marketing campaign application that integrates all the techniques discussed.
The perfect couple: Uniting Large Language Models and Knowledge Graphs for En...Neo4j
Large Language models are amazing but are also black-box models that often fail to capture and accurately represent factual knowledge. Knowledge graphs, by contrast, are structural knowledge models that explicitly represent knowledge and, indeed, allow us to detect implicit relationships. In this talk we will demonstrate how LLMs can be improved by Knowledge Graphs, and how LLM’s can augment Knowledge Graphs. A perfect couple!
Deep dive into LangChain integration with Neo4j.pptxTomazBratanic1
Deep dive into LangChain integrations with Neo4j. Learn how to query your graph with LangChain either by generating Cypher statements using LLMs or using the vector index.
The document provides an overview of knowledge graphs and the metaphactory knowledge graph platform. It defines knowledge graphs as semantic descriptions of entities and relationships using formal knowledge representation languages like RDF, RDFS and OWL. It discusses how knowledge graphs can power intelligent applications and gives examples like Google Knowledge Graph, Wikidata, and knowledge graphs in cultural heritage and life sciences. It also provides an introduction to key standards like SKOS, SPARQL, and Linked Data principles. Finally, it describes the main features and architecture of the metaphactory platform for creating and utilizing enterprise knowledge graphs.
This is Part 4 of the GoldenGate series on Data Mesh - a series of webinars helping customers understand how to move off of old-fashioned monolithic data integration architecture and get ready for more agile, cost-effective, event-driven solutions. The Data Mesh is a kind of Data Fabric that emphasizes business-led data products running on event-driven streaming architectures, serverless, and microservices based platforms. These emerging solutions are essential for enterprises that run data-driven services on multi-cloud, multi-vendor ecosystems.
Join this session to get a fresh look at Data Mesh; we'll start with core architecture principles (vendor agnostic) and transition into detailed examples of how Oracle's GoldenGate platform is providing capabilities today. We will discuss essential technical characteristics of a Data Mesh solution, and the benefits that business owners can expect by moving IT in this direction. For more background on Data Mesh, Part 1, 2, and 3 are on the GoldenGate YouTube channel: https://www.youtube.com/playlist?list=PLbqmhpwYrlZJ-583p3KQGDAd6038i1ywe
Webinar Speaker: Jeff Pollock, VP Product (https://www.linkedin.com/in/jtpollock/)
Mr. Pollock is an expert technology leader for data platforms, big data, data integration and governance. Jeff has been CTO at California startups and a senior exec at Fortune 100 tech vendors. He is currently Oracle VP of Products and Cloud Services for Data Replication, Streaming Data and Database Migrations. While at IBM, he was head of all Information Integration, Replication and Governance products, and previously Jeff was an independent architect for US Defense Department, VP of Technology at Cerebra and CTO of Modulant – he has been engineering artificial intelligence based data platforms since 2001. As a business consultant, Mr. Pollock was a Head Architect at Ernst & Young’s Center for Technology Enablement. Jeff is also the author of “Semantic Web for Dummies” and "Adaptive Information,” a frequent keynote at industry conferences, author for books and industry journals, formerly a contributing member of W3C and OASIS, and an engineering instructor with UC Berkeley’s Extension for object-oriented systems, software development process and enterprise architecture.
Data Catalog as the Platform for Data IntelligenceAlation
Data catalogs are in wide use today across hundreds of enterprises as a means to help data scientists and business analysts find and collaboratively analyze data. Over the past several years, customers have increasingly used data catalogs in applications beyond their search & discovery roots, addressing new use cases such as data governance, cloud data migration, and digital transformation. In this session, the founder and CEO of Alation will discuss the evolution of the data catalog, the many ways in which data catalogs are being used today, the importance of machine learning in data catalogs, and discuss the future of the data catalog as a platform for a broad range of data intelligence solutions.
The document discusses knowledge graphs and their value for organizations. It notes that two-thirds of Neo4j customers have implemented knowledge graphs and that 88% of CXOs believe knowledge graphs will significantly improve business outcomes. Knowledge graphs are described as interconnected datasets enriched with meaning to enable complex decision-making. Examples of how knowledge graphs have helped companies with recommendations, fraud detection, and track and trace are provided.
Data Architecture Strategies: The Rise of the Graph DatabaseDATAVERSITY
Graph databases are growing in popularity, with their ability to quickly discover and integrate key relationship between enterprise data sets. Business use cases such as recommendation engines, master data management, social networks, enterprise knowledge graphs and more provide valuable ways to leverage graph databases in your organization. This webinar provides an overview of graph database technologies, and how they can be used for practical applications to drive business value.
The State of Digital Transformation 2018 - 2019 by Brian SolisBrian Solis
"Digital is an enterprise-wide strategic priority — but there's work to be done," according to Brian Solis and Altimeter, a Prophet company.
Now in its fifth year, our annual “State of Digital Transformation” research continues to document the constantly evolving enterprise. As disruptive technologies and their impact on organizations and markets continue to progress, our research aims to capture the shifts and trends that are shaping modern digital transformation.
In 2019, strategic digital transformation is only becoming more pervasive moving beyond IT to impact competitiveness throughout the organization. Budgets are soaring. The list of disruptive technologies on the radar of stakeholders is expanding. Ownership is moving to the C-Suite and managed by cross-functional, collaborative groups. Customer experience (CX) continues to lead digital transformation investments, but as we observed in 2017, employee experience and organizational culture are also rising in importance to empower and accelerate change, growth, and innovation.
Digital Transformation as an Enterprise-Wide Movement
This year, it’s clear that digital transformation is maturing into an enterprise-wide movement. Digital transformation is modernizing how companies work and compete and helping them effectively adapt and grow in an evolving digital economy.
What’s also evident is that there is still much work to do as companies are, by and large, prioritizing technology over grasping the disruptive trends that are influencing markets and, more specifically, customer and employee behaviors and expectations.
Learn more here: https://insights.prophet.com/the-state-of-digital-transformation-2018-2019
The Future of Data Science and Machine Learning at Scale: A Look at MLflow, D...Databricks
Many had dubbed 2020 as the decade of data. This is indeed an era of data zeitgeist.
From code-centric software development 1.0, we are entering software development 2.0, a data-centric and data-driven approach, where data plays a central theme in our everyday lives.
As the volume and variety of data garnered from myriad data sources continue to grow at an astronomical scale and as cloud computing offers cheap computing and data storage resources at scale, the data platforms have to match in their abilities to process, analyze, and visualize at scale and speed and with ease — this involves data paradigm shifts in processing and storing and in providing programming frameworks to developers to access and work with these data platforms.
In this talk, we will survey some emerging technologies that address the challenges of data at scale, how these tools help data scientists and machine learning developers with their data tasks, why they scale, and how they facilitate the future data scientists to start quickly.
In particular, we will examine in detail two open-source tools MLflow (for machine learning life cycle development) and Delta Lake (for reliable storage for structured and unstructured data).
Other emerging tools such as Koalas help data scientists to do exploratory data analysis at scale in a language and framework they are familiar with as well as emerging data + AI trends in 2021.
You will understand the challenges of machine learning model development at scale, why you need reliable and scalable storage, and what other open source tools are at your disposal to do data science and machine learning at scale.
Databricks CEO Ali Ghodsi introduces Databricks Delta, a new data management system that combines the scale and cost-efficiency of a data lake, the performance and reliability of a data warehouse, and the low latency of streaming.
Data-Centric Business Transformation Using Knowledge GraphsAlan Morrison
From a talk at the Data Architecture Summit in Chicago in 2018--reviews digital transformation and what deep transformation really implies at the data layer. Cross-enterprise knowledge graphs are becoming feasible and can be a key enabler of deep transformation.
Collibra Data Citizen '19 - Bridging Data Privacy with Data Governance BigID Inc
This presentation was shown at the 2019 Collibra Data Citizen Event in New York City.
Presented by Nimrod Vax, Chief Product Officer & Co-Founder & Joaquin Sufuentes, Lead Architect, Metadata Managment and Personal Infomation Protection, enterprise Data Managment, Intel IT
Driving Talent Change for the Digital EnterprisePluralsight
This document discusses how IT roles and skills will need to change by 2020 to support digital transformation. It notes that traditional IT mindsets focused on processes, risk avoidance, and working in silos will need to shift to more adaptive, collaborative mindsets. The skills most in demand include relationship building, learning agility, creativity, and business acumen. IT staff will need more versatile technical skills and experience across different areas. Teams will also need to integrate IT and business staff to work more fluidly across functions. To develop these skills, companies should offer experience-based career paths, foster openness to change, and invest in competency development beyond traditional training.
DXC Technology https://www.dxc.technology DXC technology is the world’s leading independent, end-to-end IT services company. They lead digital transformations for clients by modernizing and integrating their mainstream IT, and by deploying digital solutions at scale to produce better business outcomes.
Embedding Employability Survey - Students
This instrument was developed from our Focus Group Consultation. It is a new survey tool, with important differences observed between stakeholders (employer, DkIT Staff, DkIT Students, DkIT Graduates). Please review each and you are welcome to modify and use for your own surveys at your own institution.
Tema Solution is a training and placement services provider focused on sectors in India requiring skilled workers. Founded in 2005 in Trichy, it has since expanded to Chennai and Coimbatore. The company understands that manpower is key to business success and works to match job seekers with employers. Tema Solution provides training for engineering fields like mechanical, aeronautical and software development. It also assists with project development, recruitment, and corporate training.
MBA Employbility pdf for vishveshwarya group of institute studentssalonibizinnovision
The Vishveshwarya Group of Institutions has a Corporate Relations & Talent Team (CRTT) that focuses on establishing relationships with over 100 reputable companies. This allows students to gain exposure through training programs at these companies. After completing the training, talented students are placed in respective companies according to their domain expertise.
Connections is a company branded employee app in Teams. It is a gateway to your employee experience, with personalized news, communications, tasks, people and resources. It provides a single curated employee destination that can be configured for specific roles like frontline workers. So, leaders can communicate and engage their employees, and employees can get easy access to the tools and resources they need from one place.. Connections builds on existing capabilities in Microsoft 365 like SharePoint and Yammer. And it pulls your communications together into a pre-configured app in Teams, designed for both desktop and mobile workers. It also acts as a launching pad to the other 3 Viva modules
Insights brings together Workplace Analytics, MyAnalytics and Glint into a unified insights app in Teams to provide data-driven and privacy-protected insights for individuals, managers and leaders. For example, employees get personalized insights, only they can see, that help them protect their time for breaks, focused work, and learning in order to promote improved productivity and wellbeing.
Topics focuses on knowledge and expertise. Topics applies AI to identify knowledge and experts and organize them into shared topics. AI automatically creates a topic page for each topic. It’s like Wikipedia for the enterprise where AI does the first draft. And these topic pages are surfaced as Topic Cards right in the flow of work in Office and Teams.
Finally, Learning allows employees to easily discover informal and formal learning in the flow of work. It aggregates content from LinkedIn Learning, Microsoft Learn and 3rd party training content and your own organizations content – all in one place. Along with providing aggregation and recommendations, it also allows managers to assign and track training, as well as report on training within and across teams.
The document describes a next-generation career management platform called Stride Ahead. It provides a data-driven career platform for students, early professionals, and talent acquisition professionals. The leadership team is described, including the co-founders and their backgrounds. Stride Ahead aims to help students and professionals better understand their interests and strengths to find the right career fit and opportunities through analysis, exploration, and evolution tools on the platform. It also helps companies and recruiters find and assess entry-level talent more efficiently.
Embedding Employability Survey - Graduates
This instrument was developed from our Focus Group Consultation. It is a new survey tool, with important differences observed between stakeholders (employer, DkIT Staff, DkIT Students, DkIT Graduates). Please review each and you are welcome to modify and use for your own surveys at your own institution.
Software Cost Estimation webinar January 2024.pdfNesma
In this webinar you will learn why Software Cost Estimation is important, what is the Software Cost Estimation Body of Knowledge for Software and the ways you can become a professional certified software cost estimator SCEC!
A skills-based approach to employment creates a more equitable job market for all. In this deck, learn how your organization can become a skills-based employer by posting positions that reflect the skills you need, selecting candidates based on their skills, and helping incumbent employees develop new skills.
View related videos:
Welcome to the Future of HCM https://www.youtube.com/watch?v=lpuYpJWD58k
One of the biggest challenges facing business today is how to attract, retain and develop the talent essential to deliver Digital Transformation.
Organisations can no longer rely on consulting or outsourcing models for Digital transformations and recognise they have to build internal capability as a business imperative.
The Mindscape-AI business model allows us to support our clients in their desire to hire, train and develop their own internal Digital capability. We would welcome the opportunity to explore where we can bring value to you and to share our approach in more detail.
We work with our clients to develop bespoke training & development programmes which are delivered over three months. Once deployed on site with our clients, we are responsible for managing the transition from Mindscape-AI consultant to permanent digital employee for our
Our model is designed to allow our clients transition our cohorts to permanent members of staff, whenever that works. As well as being cost effective, there is no vested interest in longevity of tenure. Our Digital Cohorts are built not bought and we guide them along the Deep Pathway until our clients are ready to transition and embed.
We offer a highly flexible approach to transitioning our consultants to permanent positions within your digital teams providing early conversion opportunities at 3, 6, 9 and 12 months.
Areas where we can help are:
Salesforce, Data Science and Analytics, AI and Machine Learning, Robotic Process Automation, Blockchain, Cyber Security, Java and .Net, SAP.
Email Mike@perspectivechange.com for an exploratory discussion
Perspective Change Consulting are the authorised go to market partner of Mindscape-A1
Since inception in Feb 2010, Sixth Dimension Learning (SDL) has trained thousands professionals in Canada. We offer education of outstanding quality in the field of Project Management, Business Analysis, Business Analysis Modeling, ITIL, Six Sigma Green Belt, and various other management / technology related subjects. Many of these courses lead to professional certifications that are highly valued by the industry. Apart from training individuals, we also offer corporate training. Training is our profession, but we do it with a lot of fervor and passion, which clearly separates us from many. Also we train in small groups to ensure highest levels of knowledge transfer. We believe for effective knowledge transfer the optimal student-teacher ratio should be around 6 to 8.
Happiest Minds is a digital transformation, security and product engineering company with over 700K investors and 55 Fortune 2000/Forbes 200 clients. It has completed 11 years in business and has a strong management team and corporate governance. Happiest Minds has over 3,500 employees across 7 countries and focuses on disruptive technologies like AI, blockchain, IoT, and more. It has received several awards for its culture, workplace practices, and corporate governance.
Embedding Employability Survey - Staff
This instrument was developed from our Focus Group Consultation. It is a new survey tool, with important differences observed between stakeholders (employer, DkIT Staff, DkIT Students, DkIT Graduates). Please review each and you are welcome to modify and use for your own surveys at your own institution.
TalentView Digital Demo Day: Building Graduate Recruitment Programs That Deli...TalentView
While we also want to thank the audience, let's still keep a standard on the copies for our assets
Need to attract graduate talents but don’t know where to start?
To attract new talents that will suit the job, there are certain factors you should consider like what satisfies them and what kind of working environment they are looking for.
In this 1 hour session, we discussed key strategies and best practices for creating an effective graduate recruitment program that can help you:
1. Understand graduate hires' preferences and priorities
2. Increase engagement with graduate talent
3. Innovate your program to attract and hire the best-in-class talent
Thank you to everyone who attended the Digital Demo Day! We hope that you found these discussion points insightful and useful for your own organizations.
We look forward to hosting more informative events in the future! #TalentViewLearning
For any questions or inquiries, email us at inquiry@talentview.com
Watch the replay recording here: https://www.talentview.com/digital-demo-day-building-a-graduate-recruitment-program-that-delivers/
Syed Wahab Ali Qadri has over 6 years of experience in information technology with expertise in areas such as project management, IT infrastructure, software handling, ERP technical support, and business analysis. He holds professional certifications in CCNA, ERP Dynamics AX 2012, and has a BSCS degree. Qadri is currently seeking a managerial position that makes use of his skills and experiences while allowing for personal development.
The document summarizes a company's path to agility after a merger. It discusses the challenges they faced with customers, talent, and competition. Their solution was to implement an agile transformation with themes of bringing out the best in employees, organizing for innovation, and enhancing capabilities through learning. Key aspects of the transformation included establishing mission teams, improving skills through training and self-directed learning, and delivering value to customers through frequent iteration.
The document summarizes a company's path to agility after a merger. It discusses challenges around serving customers and competing against larger competitors. The company addressed these challenges by implementing an agile transformation with themes of bringing out the best in employees, organizing for innovation, and enhancing capabilities through learning and iteration. Teams were restructured, processes improved, and individuals empowered to help the merged company compete and innovate more effectively.
The document summarizes an informational session about opportunities in the software industry and a new program called Shifting Code. Shifting Code is a 12-week program that will provide coding instruction and real-world projects to help candidates gain skills and employment in the software industry. The session featured presentations from regional employers, information about different types of software jobs and career paths, and details about applying for and participating in the Shifting Code program.
Similar to Using an employee knowledge graph for employee engagement and career mobility (20)
Atelier - Architecture d’applications de Graphes - GraphSummit ParisNeo4j
Atelier - Architecture d’applications de Graphes
Participez à cet atelier pratique animé par des experts de Neo4j qui vous guideront pour découvrir l’intelligence contextuelle. En utilisant un jeu de données réel, nous construirons étape par étape une solution de graphes ; de la construction du modèle de données de graphes à l’exécution de requêtes et à la visualisation des données. L’approche sera applicable à de multiples cas d’usages et industries.
Atelier - Innover avec l’IA Générative et les graphes de connaissancesNeo4j
Atelier - Innover avec l’IA Générative et les graphes de connaissances
Allez au-delà du battage médiatique autour de l’IA et découvrez des techniques pratiques pour utiliser l’IA de manière responsable à travers les données de votre organisation. Explorez comment utiliser les graphes de connaissances pour augmenter la précision, la transparence et la capacité d’explication dans les systèmes d’IA générative. Vous partirez avec une expérience pratique combinant les relations entre les données et les LLM pour apporter du contexte spécifique à votre domaine et améliorer votre raisonnement.
Amenez votre ordinateur portable et nous vous guiderons sur la mise en place de votre propre pile d’IA générative, en vous fournissant des exemples pratiques et codés pour démarrer en quelques minutes.
Neo4j - Product Vision and Knowledge Graphs - GraphSummit ParisNeo4j
Dr. Jesús Barrasa, Head of Solutions Architecture for EMEA, Neo4j
Découvrez les dernières innovations de Neo4j, et notamment les dernières intégrations cloud et les améliorations produits qui font de Neo4j un choix essentiel pour les développeurs qui créent des applications avec des données interconnectées et de l’IA générative.
Neo4j - Product Vision and Knowledge Graphs - GraphSummit ParisNeo4j
Dr. Jesús Barrasa, Head of Solutions Architecture for EMEA, Neo4j
Découvrez les dernières innovations de Neo4j, et notamment les dernières intégrations cloud et les améliorations produits qui font de Neo4j un choix essentiel pour les développeurs qui créent des applications avec des données interconnectées et de l’IA générative.
SOPRA STERIA - GraphRAG : repousser les limitations du RAG via l’utilisation ...Neo4j
Romain CAMPOURCY – Architecte Solution, Sopra Steria
Patrick MEYER – Architecte IA Groupe, Sopra Steria
La Génération de Récupération Augmentée (RAG) permet la réponse à des questions d’utilisateur sur un domaine métier à l’aide de grands modèles de langage. Cette technique fonctionne correctement lorsque la documentation est simple mais trouve des limitations dès que les sources sont complexes. Au travers d’un projet que nous avons réalisé, nous vous présenterons l’approche GraphRAG, une nouvelle approche qui utilise une base Neo4j générée pour améliorer la compréhension des documents et la synthèse d’informations. Cette méthode surpasse l’approche RAG en fournissant des réponses plus holistiques et précises.
ADEO - Knowledge Graph pour le e-commerce, entre challenges et opportunités ...Neo4j
Charles Gouwy, Business Product Leader, Adeo Services (Groupe Leroy Merlin)
Alors que leur Knowledge Graph est déjà intégré sur l’ensemble des expériences d’achat de leur plateforme e-commerce depuis plus de 3 ans, nous verrons quelles sont les nouvelles opportunités et challenges qui s’ouvrent encore à eux grâce à leur utilisation d’une base de donnée de graphes et l’émergence de l’IA.
GraphSummit Paris - The art of the possible with Graph TechnologyNeo4j
Sudhir Hasbe, Chief Product Officer, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
GraphAware - Transforming policing with graph-based intelligence analysisNeo4j
Petr Matuska, Sales & Sales Engineering Lead, GraphAware
Western Australia Police Force’s adoption of Neo4j and the GraphAware Hume graph analytics platform marks a significant advancement in data-driven policing. Facing the challenges of growing volumes of valuable data scattered in disconnected silos, the organisation successfully implemented Neo4j database and Hume, consolidating data from various sources into a dynamic knowledge graph. The result was a connected view of intelligence, making it easier for analysts to solve crime faster. The partnership between Neo4j and GraphAware in this project demonstrates the transformative impact of graph technology on law enforcement’s ability to leverage growing volumes of valuable data to prevent crime and protect communities.
GraphSummit Stockholm - Neo4j - Knowledge Graphs and Product UpdatesNeo4j
David Pond, Lead Product Manager, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
Shirley Bacso, Data Architect, Ingka Digital
“Linked Metadata by Design” represents the integration of the outcomes from human collaboration, starting from the design phase of data product development. This knowledge is captured in the Data Knowledge Graph. It not only enables data products to be robust and compliant but also well-understood and effectively utilized.
Your enemies use GenAI too - staying ahead of fraud with Neo4jNeo4j
Delivered by Michael Down at Gartner Data & Analytics Summit London 2024 - Your enemies use GenAI too: Staying ahead of fraud with Neo4j.
Fraudsters exploit the latest technologies like generative AI to stay undetected. Static applications can’t adapt quickly enough. Learn why you should build flexible fraud detection apps on Neo4j’s native graph database combined with advanced data science algorithms. Uncover complex fraud patterns in real-time and shut down schemes before they cause damage.
BT & Neo4j _ How Knowledge Graphs help BT deliver Digital Transformation.pptxNeo4j
Delivered by Sreenath Gopalakrishna, Director of Software Engineering at BT, and Dr Jim Webber, Chief Scientist at Neo4j, at Gartner Data & Analytics Summit London 2024 this presentation examines how knowledge graphs and GenAI combine in real-world solutions.
BT Group has used the Neo4j Graph Database to enable impressive digital transformation programs over the last 6 years. By re-imagining their operational support systems to adopt self-serve and data lead principles they have substantially reduced the number of applications and complexity of their operations. The result has been a substantial reduction in risk and costs while improving time to value, innovation, and process automation. Future innovation plans include the exploration of uses of EKG + Generative AI.
Workshop: Enabling GenAI Breakthroughs with Knowledge Graphs - GraphSummit MilanNeo4j
Look beyond the hype and unlock practical techniques to responsibly activate intelligence across your organization’s data with GenAI. Explore how to use knowledge graphs to increase accuracy, transparency, and explainability within generative AI systems. You’ll depart with hands-on experience combining relationships and LLMs for increased domain-specific context and enhanced reasoning.
Takashi Kobayashi and Hironori Washizaki, "SWEBOK Guide and Future of SE Education," First International Symposium on the Future of Software Engineering (FUSE), June 3-6, 2024, Okinawa, Japan
Artificia Intellicence and XPath Extension FunctionsOctavian Nadolu
The purpose of this presentation is to provide an overview of how you can use AI from XSLT, XQuery, Schematron, or XML Refactoring operations, the potential benefits of using AI, and some of the challenges we face.
SOCRadar's Aviation Industry Q1 Incident Report is out now!
The aviation industry has always been a prime target for cybercriminals due to its critical infrastructure and high stakes. In the first quarter of 2024, the sector faced an alarming surge in cybersecurity threats, revealing its vulnerabilities and the relentless sophistication of cyber attackers.
SOCRadar’s Aviation Industry, Quarterly Incident Report, provides an in-depth analysis of these threats, detected and examined through our extensive monitoring of hacker forums, Telegram channels, and dark web platforms.
Do you want Software for your Business? Visit Deuglo
Deuglo has top Software Developers in India. They are experts in software development and help design and create custom Software solutions.
Deuglo follows seven steps methods for delivering their services to their customers. They called it the Software development life cycle process (SDLC).
Requirement — Collecting the Requirements is the first Phase in the SSLC process.
Feasibility Study — after completing the requirement process they move to the design phase.
Design — in this phase, they start designing the software.
Coding — when designing is completed, the developers start coding for the software.
Testing — in this phase when the coding of the software is done the testing team will start testing.
Installation — after completion of testing, the application opens to the live server and launches!
Maintenance — after completing the software development, customers start using the software.
Using Query Store in Azure PostgreSQL to Understand Query PerformanceGrant Fritchey
Microsoft has added an excellent new extension in PostgreSQL on their Azure Platform. This session, presented at Posette 2024, covers what Query Store is and the types of information you can get out of it.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Transform Your Communication with Cloud-Based IVR SolutionsTheSMSPoint
Discover the power of Cloud-Based IVR Solutions to streamline communication processes. Embrace scalability and cost-efficiency while enhancing customer experiences with features like automated call routing and voice recognition. Accessible from anywhere, these solutions integrate seamlessly with existing systems, providing real-time analytics for continuous improvement. Revolutionize your communication strategy today with Cloud-Based IVR Solutions. Learn more at: https://thesmspoint.com/channel/cloud-telephony
E-commerce Application Development Company.pdfHornet Dynamics
Your business can reach new heights with our assistance as we design solutions that are specifically appropriate for your goals and vision. Our eCommerce application solutions can digitally coordinate all retail operations processes to meet the demands of the marketplace while maintaining business continuity.
AI Fusion Buddy Review: Brand New, Groundbreaking Gemini-Powered AI AppGoogle
AI Fusion Buddy Review: Brand New, Groundbreaking Gemini-Powered AI App
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See My Other Reviews Article:
(1) AI Genie Review: https://sumonreview.com/ai-genie-review
(2) SocioWave Review: https://sumonreview.com/sociowave-review
(3) AI Partner & Profit Review: https://sumonreview.com/ai-partner-profit-review
(4) AI Ebook Suite Review: https://sumonreview.com/ai-ebook-suite-review
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DDS Security Version 1.2 was adopted in 2024. This revision strengthens support for long runnings systems adding new cryptographic algorithms, certificate revocation, and hardness against DoS attacks.
UI5con 2024 - Keynote: Latest News about UI5 and it’s EcosystemPeter Muessig
Learn about the latest innovations in and around OpenUI5/SAPUI5: UI5 Tooling, UI5 linter, UI5 Web Components, Web Components Integration, UI5 2.x, UI5 GenAI.
Recording:
https://www.youtube.com/live/MSdGLG2zLy8?si=INxBHTqkwHhxV5Ta&t=0
E-Invoicing Implementation: A Step-by-Step Guide for Saudi Arabian CompaniesQuickdice ERP
Explore the seamless transition to e-invoicing with this comprehensive guide tailored for Saudi Arabian businesses. Navigate the process effortlessly with step-by-step instructions designed to streamline implementation and enhance efficiency.
E-commerce Development Services- Hornet DynamicsHornet Dynamics
For any business hoping to succeed in the digital age, having a strong online presence is crucial. We offer Ecommerce Development Services that are customized according to your business requirements and client preferences, enabling you to create a dynamic, safe, and user-friendly online store.