Visualize the Knowledge Graph and Unleash Your Data
•
3 likes•523 views
Slides from the webinar "Visualize the Knowledge Graph and Unleash Your Data" with Michael Grove, Vice President of Engineering and co-founder of Stardog, and Jean Villedieu, co-founder of Linkurious. The webinar covers the topic of enterprise Knowledge Graphs and lets you experience how to visualize and analyze this data to discover actionable insights for your organization.
Report
Share
Report
Share
Download to read offline
Recommended
Graph-based Network & IT Management.
Maintaining networks and servers availability while reducing downtimes to minimum are fundamental missions for IT managers and administrators. But with the growing complexity of infrastructures, the pressure from business strategists to deliver new services or the heterogeneity of data assets, managing networks is often a challenge.
Graph technologies like Linkurious offer an intuitive approach to model and investigate data by putting the connections between components at the forefront. Modeling the network into a flexible and unified overview is one of the keys to understand your architecture and reduce risks, costs and time spent on maintenance operations.
How to visualize Cosmos DB graph data
Linkurious Enterprise is compatible with Azure Cosmos DB and offers investigation teams a turnkey solution to detect and investigate threats hidden in graph data. In this post, we explain how Linkurious Enterprise connects to Cosmos DB graph database.
Graph-based Product Lifecycle Management
Supporting product development while reducing material and prototyping costs or centralizing product records is critical for PLM and PDM managers. However, the growing complexity and volume of cross-business data and processes can turn the management of a product lifecycle into a complex enterprise.
Graph technology like Linkurious offers an intuitive approach to model, search and understand data by putting the connections between components at the forefront. Modeling people, processes, business systems and products components into an interactive and unified network is one of the keys to escape the complexity of product development and find the insights your organization need to gain competitive advantage.
In this presentation, you will learn about:
- Challenges and risks of product development and data management,
- How businesses can use graph technology to model, visualize, optimize and monitor product lifecycles and related elements,
- How to conduct BOM and change management with Linkurious.
Getting started with Cosmos DB + Linkurious Enterprise
Nowadays, many real-world applications generate data that is naturally connected, but traditional systems fail to capture the value it represents. Thanks to its graph API, the multi-model database Cosmos DB lets you model and store graph-like data. On top of Cosmos DB, Linkurious Enterprise is turnkey solution to detect and investigate insights through an interface for graph data visualization and analysis.
In this presentation, we will explain the value of graphs and show how to get started with Cosmos DB and Linkurious Enterprise to accelerate the discovery of new insights in your connected data.
Using Linkurious in your Enterprise Architecture projects
Architects, analysts and business managers need comprehensive modeling and visualization tools to understand how companies assets are assembled. Graph technologies allow to understand complex connected data and manage change and complexity in a more efficient way than traditional siloed solutions. With Linkurious technology, you get a comprehensive and visual overview of your enterprise architecture to successfully implement new systems, processes or frameworks.
The years of the graph: The future of the future is here
What is graph all about, and why should you care? Graphs come in many shapes and forms, and can be used for different applications: Graph Analytics, Graph AI, Knowledge Graphs, and Graph Databases.
Talk by George Anadiotis. Connected Data London Meetup June 29th 2020.
Up until the beginning of the 2010s, the world was mostly running on spreadsheets and relational databases. To a large extent, it still does. But the NoSQL wave of databases has largely succeeded in instilling the “best tool for the job” mindset.
After relational, key-value, document, and columnar, the latest link in this evolutionary proliferation of data structures is graph. Graph analytics, Graph AI, Knowledge Graphs and Graph Databases have been making waves, included in hype cycles for the last couple of years.
The Year of the Graph marked the beginning of it all before the Gartners of the world got in the game. The Year of the Graph is a term coined to convey the fact that the time has come for this technology to flourish.
The eponymous article that set the tone was published in January 2018 on ZDNet by domain expert George Anadiotis. George has been working with, and keeping an eye on, all things Graph since the early 2000s. He was one of the first to note the continuing rise of Graph Databases, and to bring this technology in front of a mainstream audience.
The Year of the Graph has been going strong since 2018. In August 2018, Gartner started including Graph in its hype cycles. Ever since, Graph has been riding the upward slope of the Hype Cycle.
The need for knowledge on these technologies is constantly growing. To respond to that need, the Year of the Graph newsletter was released in April 2018. In addition, a constant flow of graph-related news and resources is being shared on social media.
To help people make educated choices, the Year of the Graph Database Report was released. The report has been hailed as the most comprehensive of its kind in the market, consistently helping people choose the most appropriate solution for their use case since 2018.
The report, articles, news stream, and the newsletter have been reaching thousands of people, helping them understand and navigate this landscape. We’ll talk about the Year of the Graph, the different shapes, forms, and applications for graphs, the latest news and trends, and wrap up with an ask me anything session.
Enterprise Data Governance: Leveraging Knowledge Graph & AI in support of a d...
Enterprise Data Governance: Leveraging Knowledge Graph & AI in support of a d...Connected Data World
As one of the largest financial institutions worldwide, JP Morgan is reliant on data to drive its day-to-day operations, against an ever evolving regulatory regime. Our global data landscape possesses particular challenges of effectively maintaining data governance and metadata management.
The Data strategy at JP Morgan intends to:
a) generate business value
b) adhere to regulatory & compliance requirements
c) reduce barriers to access
d) democratize access to data
In this talk, we show how JP Morgan leverages semantic technologies to drive the implementation of our data strategy. We demonstrate how we exploit knowledge graph capabilities to answer:
1) What Data do I need?
2) What Data do we have?
3) Where does my Data come from?
4) Where should my Data come from?
5) What Data should be shared most?Graph Realities
Graph applications were once considered “exotic” and expensive. Until recently, few software engineers had much experience putting graphs to work. However, the use cases are now becoming more commonplace.
This talk explores a practical use case, one which addresses key issues of data governance and reproducible research, and depends on sophisticated use of graph technology.
Consider: some academic disciplines such as astronomy enjoy a wealth of data — mostly open data. Popular machine learning algorithms, open source Python libraries, and distributed systems all owe much to those disciplines and their history of big data.
Other disciplines require strong guarantees for privacy and security. Datasets used in social science research involve confidential details about human subjects: medical histories, wages, home addresses for family members, police records, etc.
Those cannot be shared openly, which impedes researchers from learning about related work by others. Reproducibility of research and the pace of science in general are limited. Nonetheless, social science research is vital for civil governance, especially for evidence-based policymaking (US federal law since 2018).
Even when data may be too sensitive to share openly, often the metadata can be shared. Constructing knowledge graphs of metadata about datasets — along with metadata about authors, their published research, methods used, data providers, data stewards, and so on — that provides effective means to tackle hard problems in data governance.
Knowledge graph work supports use cases such as entity linking, discovery and recommendations, axioms to infer about compliance, etc. This talk reviews the Rich Context AI competition and the related ADRF framework used now by more than 15 federal agencies in the US.
We’ll explore knowledge graph use cases, use of open standards and open source, and how this enhances reproducible research. Social science research for the public sector has much in common with data use in industry.
Issues of privacy, security, and compliance overlap, pointing toward what will be required of banks, media channels, etc., and what technologies apply. We’ll look at comparable work emerging in other parts of industry: open source projects, open standards emerging, and in particular a new set of features in Project Jupyter that support knowledge graphs about data governance.
Recommended
Graph-based Network & IT Management.
Maintaining networks and servers availability while reducing downtimes to minimum are fundamental missions for IT managers and administrators. But with the growing complexity of infrastructures, the pressure from business strategists to deliver new services or the heterogeneity of data assets, managing networks is often a challenge.
Graph technologies like Linkurious offer an intuitive approach to model and investigate data by putting the connections between components at the forefront. Modeling the network into a flexible and unified overview is one of the keys to understand your architecture and reduce risks, costs and time spent on maintenance operations.
How to visualize Cosmos DB graph data
Linkurious Enterprise is compatible with Azure Cosmos DB and offers investigation teams a turnkey solution to detect and investigate threats hidden in graph data. In this post, we explain how Linkurious Enterprise connects to Cosmos DB graph database.
Graph-based Product Lifecycle Management
Supporting product development while reducing material and prototyping costs or centralizing product records is critical for PLM and PDM managers. However, the growing complexity and volume of cross-business data and processes can turn the management of a product lifecycle into a complex enterprise.
Graph technology like Linkurious offers an intuitive approach to model, search and understand data by putting the connections between components at the forefront. Modeling people, processes, business systems and products components into an interactive and unified network is one of the keys to escape the complexity of product development and find the insights your organization need to gain competitive advantage.
In this presentation, you will learn about:
- Challenges and risks of product development and data management,
- How businesses can use graph technology to model, visualize, optimize and monitor product lifecycles and related elements,
- How to conduct BOM and change management with Linkurious.
Getting started with Cosmos DB + Linkurious Enterprise
Nowadays, many real-world applications generate data that is naturally connected, but traditional systems fail to capture the value it represents. Thanks to its graph API, the multi-model database Cosmos DB lets you model and store graph-like data. On top of Cosmos DB, Linkurious Enterprise is turnkey solution to detect and investigate insights through an interface for graph data visualization and analysis.
In this presentation, we will explain the value of graphs and show how to get started with Cosmos DB and Linkurious Enterprise to accelerate the discovery of new insights in your connected data.
Using Linkurious in your Enterprise Architecture projects
Architects, analysts and business managers need comprehensive modeling and visualization tools to understand how companies assets are assembled. Graph technologies allow to understand complex connected data and manage change and complexity in a more efficient way than traditional siloed solutions. With Linkurious technology, you get a comprehensive and visual overview of your enterprise architecture to successfully implement new systems, processes or frameworks.
The years of the graph: The future of the future is here
What is graph all about, and why should you care? Graphs come in many shapes and forms, and can be used for different applications: Graph Analytics, Graph AI, Knowledge Graphs, and Graph Databases.
Talk by George Anadiotis. Connected Data London Meetup June 29th 2020.
Up until the beginning of the 2010s, the world was mostly running on spreadsheets and relational databases. To a large extent, it still does. But the NoSQL wave of databases has largely succeeded in instilling the “best tool for the job” mindset.
After relational, key-value, document, and columnar, the latest link in this evolutionary proliferation of data structures is graph. Graph analytics, Graph AI, Knowledge Graphs and Graph Databases have been making waves, included in hype cycles for the last couple of years.
The Year of the Graph marked the beginning of it all before the Gartners of the world got in the game. The Year of the Graph is a term coined to convey the fact that the time has come for this technology to flourish.
The eponymous article that set the tone was published in January 2018 on ZDNet by domain expert George Anadiotis. George has been working with, and keeping an eye on, all things Graph since the early 2000s. He was one of the first to note the continuing rise of Graph Databases, and to bring this technology in front of a mainstream audience.
The Year of the Graph has been going strong since 2018. In August 2018, Gartner started including Graph in its hype cycles. Ever since, Graph has been riding the upward slope of the Hype Cycle.
The need for knowledge on these technologies is constantly growing. To respond to that need, the Year of the Graph newsletter was released in April 2018. In addition, a constant flow of graph-related news and resources is being shared on social media.
To help people make educated choices, the Year of the Graph Database Report was released. The report has been hailed as the most comprehensive of its kind in the market, consistently helping people choose the most appropriate solution for their use case since 2018.
The report, articles, news stream, and the newsletter have been reaching thousands of people, helping them understand and navigate this landscape. We’ll talk about the Year of the Graph, the different shapes, forms, and applications for graphs, the latest news and trends, and wrap up with an ask me anything session.
Enterprise Data Governance: Leveraging Knowledge Graph & AI in support of a d...
Enterprise Data Governance: Leveraging Knowledge Graph & AI in support of a d...Connected Data World
As one of the largest financial institutions worldwide, JP Morgan is reliant on data to drive its day-to-day operations, against an ever evolving regulatory regime. Our global data landscape possesses particular challenges of effectively maintaining data governance and metadata management.
The Data strategy at JP Morgan intends to:
a) generate business value
b) adhere to regulatory & compliance requirements
c) reduce barriers to access
d) democratize access to data
In this talk, we show how JP Morgan leverages semantic technologies to drive the implementation of our data strategy. We demonstrate how we exploit knowledge graph capabilities to answer:
1) What Data do I need?
2) What Data do we have?
3) Where does my Data come from?
4) Where should my Data come from?
5) What Data should be shared most?Graph Realities
Graph applications were once considered “exotic” and expensive. Until recently, few software engineers had much experience putting graphs to work. However, the use cases are now becoming more commonplace.
This talk explores a practical use case, one which addresses key issues of data governance and reproducible research, and depends on sophisticated use of graph technology.
Consider: some academic disciplines such as astronomy enjoy a wealth of data — mostly open data. Popular machine learning algorithms, open source Python libraries, and distributed systems all owe much to those disciplines and their history of big data.
Other disciplines require strong guarantees for privacy and security. Datasets used in social science research involve confidential details about human subjects: medical histories, wages, home addresses for family members, police records, etc.
Those cannot be shared openly, which impedes researchers from learning about related work by others. Reproducibility of research and the pace of science in general are limited. Nonetheless, social science research is vital for civil governance, especially for evidence-based policymaking (US federal law since 2018).
Even when data may be too sensitive to share openly, often the metadata can be shared. Constructing knowledge graphs of metadata about datasets — along with metadata about authors, their published research, methods used, data providers, data stewards, and so on — that provides effective means to tackle hard problems in data governance.
Knowledge graph work supports use cases such as entity linking, discovery and recommendations, axioms to infer about compliance, etc. This talk reviews the Rich Context AI competition and the related ADRF framework used now by more than 15 federal agencies in the US.
We’ll explore knowledge graph use cases, use of open standards and open source, and how this enhances reproducible research. Social science research for the public sector has much in common with data use in industry.
Issues of privacy, security, and compliance overlap, pointing toward what will be required of banks, media channels, etc., and what technologies apply. We’ll look at comparable work emerging in other parts of industry: open source projects, open standards emerging, and in particular a new set of features in Project Jupyter that support knowledge graphs about data governance.
From Knowledge Graphs to AI-powered SEO: Using taxonomies, schemas and knowle...
From Knowledge Graphs to AI-powered SEO: Using taxonomies, schemas and knowle...Connected Data World
Do you want to learn how to use the low-hanging fruit of knowledge graphs — schema.org and JSON-LD — to annotate content and improve your SEO with semantics and entities? This hands-on workshop with one of the leading Semantic SEO practitioners will help you get started.Graph-based intelligence analysis
For decades, the intelligence community has been collecting and analyzing information to produce timely and actionable insights for intelligence consumers. But as the amount of information collected increases, analysts are facing new challenges in terms of data processing and analysis. In this presentation, we explore the possibilities that graph technology is offering for intelligence analysis.
Knowledge Graphs Webinar- 11/7/2017
A webinar on how Neo4j customers like Nasa, AirBnB, eBay, government agencies, investigative journalists and others are building Knowledge Graphs to inform today and tomorrow’s solutions.
Combining a Knowledge Graph and Graph Algorithms to Find Hidden Skills at NASA
Speaker: David Meza, Sr. Data Scientist, NASA
Enterprise Knowledge Graph
by Lukas Masuch, Henning Muszynski and Benjamin Raethlein
The Enterprise Knowledge Graph is a disruptive platform that combines emerging Big Data and Graph technologies to reinvent knowledge management inside organizations. This platform aims to organize and distribute the organization’s knowledge, and making it centralized and universally accessible to every employee. The Enterprise Knowledge Graph is a central place to structure, simplify and connect the knowledge of an organization. By removing complexity, the knowledge graph brings more transparency, openness and simplicity into organizations. That leads to democratized communications and empowers individuals to share knowledge and to make decisions based on comprehensive knowledge. This platform can change the way we work, challenge the traditional hierarchical approach to get work done and help to unleash human potential!
Using graph technology for multi-INT investigations
Learn how to break silos and reduce complexity in Multi-INT investigations with graphs.
Graphs in Telecommunications - Jesus Barrasa, Neo4j
Graphs in Telecommunications
Jesús Barrasa, Neo4j
Big Data Fabric 2.0 Drives Data Democratization
In their webinar "Big Data Fabric 2.0 Drives Data Democratization" Ben Szekley, Cambridge Semantics’ SVP of Field Operations, and guest speaker, Forrester’s Noel Yuhanna, author of the Forrester report: “Big Data Fabric 2.0 Drives Data Democratization”, explored why data-driven businesses are making a big data fabric part of their data strategy to minimize data complexity, integrate siloed data, deliver real-time trusted insights, and to create new business opportunities. These are the slides from that webinar.
Big Data Landscape 2016
Annual Big Data Landscape prepared by FIrstMark. Check out full blog post: "Is Big Data Still a Thing"? at http://mattturck.com/2016/02/01/big-data-landscape/
Using a Semantic and Graph-based Data Catalog in a Modern Data Fabric
Watch this webinar to learn about the benefits of using semantic and graph database technology to create a Data Catalog of all of an enterprise's data, regardless of source or format, as part of a modern IT or data management stack and an important step toward building an Enterprise Data Fabric.
How Semantics Solves Big Data Challenges
Today, organizations want both IT simplicity and innovation, but reliance on traditional databases only leads to more complexity, longer development cycles, and more silos. In fact, organizations report that the #1 impediment to big data success is having too many silos. In this webinar, we will discuss how a new database technology, semantics, solves this problem by providing a new approach to modeling data that focuses on relationships and context, making it easier for data to be understood, searched, and shared. With semantics, world-leading organizations are integrating disparate data faster and easier and building smarter applications with richer analytic capabilities—benefits that we look forward to diving into during the webinar.
Linking SharePoint Documents with Structured Data
Unified views of business-critical information across all customer-facing processes and HR-related tasks are most relevant for decision makers.
In this talk we present a SharePoint extension that supports the automatic linking of unstructured content like Word documents with structured information from other databases, such as statistical data. As a result, decision makers have knowledge portals based on linked data at their fingertips.
While the importance of managed metadata and Term Store is clear to most SharePoint architects, the significance of a semantic layer outside of the content silos has not yet been explored systematically.
We will present a four-layered content architecture and will take a close look on some of the aspects of the semantic layer and its integration with SharePoint:
- Keeping Term Store and the semantic layer in sync
- Automatic tagging of SharePoint content
- Use of graph databases to store tags
- Entity-centric search & analytics applications
Metadata is most often stored per data source, and therefore it is meaningless outside of the silo. In this presentation, we will give a live demo of a SharePoint extension that makes use of an explicit semantic layer based on standards. This approach builds the basis to start linking data across the silos in a most agile way.
The resulting knowledge graph can start on a small scale, to develop continuously and to grow with the requirements. In this presentation we will give an example to illustrate how initially disconnected HR-related data (CVs in SharePoint; statistical data from labour market; skills and competencies taxonomies; salary spreadsheets) gets linked automatically, and is then made available through an extensive search & analytics application.
Risk Analytics Using Knowledge Graphs / FIBO with Deep Learning
This EDM Council webinar, sponsored by Cambridge Semantics Inc. and featuring FI Consulting, explores the challenges common to a risk analytics pipeline, application of graph analytics to mortgage loan data and use cases in adjacent areas including customer service, collections, fraud and AML.
NoSQL Technology and Real-time, Accurate Predictive Analytics
Big Data: NoSQL Technology and Real-time, Accurate Predictive Analytics
Enjoy this insightful webinar moderated by Matt Aslett, Research Director at 451 Group beginning with a brief overview of Objectivity, Inc. and its products Objectivity/DB, a world class object database and InfiniteGraph, the enterprise proven, scalable and distributed graph database with deployments across multiple major verticals including government, telecom, finance, security, and social networking. Learn how Georgetown University is taking advantage of Objectivity’s products to develop one of the most interconnected databases today. Examining information from all types of sources worldwide in real-time.
J.C. Smart, Director Global Insight Laboratory, Georgetown University- Coming Soon
Leon Guzenda, Founder, Objectivity – a founding member of Objectivity, Inc. in 1988, one of the original architects of Objectivity/DB and Chief Technology Officer. He now consults with the company and works with Objectivity’s Big Data and Analytics customers/partners to deploy Objectivity/DB and InfiniteGraph, a high performance, scalable graph database.
Matt Aslett, Research Director, 451 Group – As Research Director for data management and analytics within 451 Research’s Information Management practice, Matt has overall responsibility for the coverage of operational and analytic databases, data integration, data quality, and business intelligence. Matt’s own primary area of focus is on relational and non-relational databases, data warehousing, data caching, and Hadoop. Matthew is also an expert in open source software and regularly contributes to 451 Research’s open source-related research.
Graph technology and data-journalism: the case of the Paradise Papers
Discover how graph analysis and visualization technologies allowed the ICIJ journalists to highlight the suspicious relations between political figures and offshore companies in the Paradise Papers investigations.
From Taxonomies and Schemas to Knowledge Graphs: Parts 1 & 2
Do you have experience in data modeling, or using taxonomies to classify things, and want to upgrade to modeling knowledge graphs? This hands-on workshop with one of the leading knowledge graph practitioners will help you get started.
Parts 1 & 2
BrightTALK - Semantic AI
Bringing Machine Learning and Knowledge Graphs Together
Six Core Aspects of Semantic AI:
- Hybrid Approach
- Data Quality
- Data as a Service
- Structured Data Meets Text
- No Black-box
- Towards Self-optimizing Machines
Leveraging Knowledge Graphs in your Enterprise Knowledge Management System
Knowledge graphs and graph-based data in general are becoming increasingly important for addressing various data management challenges in industries such as financial services, life sciences, healthcare or energy.
At the core of this challenge is the comprehensive management of graph-based data, ranging from taxonomy to ontology management to the administration of comprehensive data graphs along with a defined governance framework. Various data sources are integrated and linked (semi) automatically using NLP and machine learning algorithms. Tools for securing high data quality and consistency are an integral part of such a platform.
PoolParty 7.0 can now handle a full range of enterprise data management tasks. Based on agile data integration, machine learning and text mining, or ontology-based data analysis, applications are developed that allow knowledge workers, marketers, analysts or researchers a comprehensive and in-depth view of previously unlinked data assets.
At the heart of the new release is the PoolParty GraphEditor, which complements the Taxonomy, Thesaurus, and Ontology Manager components that have been around for some time. All in all, data engineers and subject matter experts can now administrate and analyze enterprise-wide and heterogeneous data stocks with comfortable means, or link them with the help of artificial intelligence.
Graph Databases – Benefits and Risks
Graph databases provide the ability to quickly discover and integrate key relationships between enterprise data sets. Business use cases such as recommendation engines, social networks, enterprise knowledge graphs, and more provide valuable ways to leverage graph databases in your organization. This webinar will provide an overview of graph database technologies, and how they can be used for practical applications to drive business value.
Impulser la digitalisation et modernisation de la fonction Finance grâce à la...
Voir: https://bit.ly/2Oycfnn
À l’ère du numérique, la digitalisation et modernisation des services financiers sont plus que jamais requises compte tenu de leur rôle clé dans les processus de prise de décisions et le pilotage de la performance. Les directions financières nécessitent ainsi de fournir des informations fiables et vérifiées, tout en répondant aux exigences de gouvernance et de sécurité. À cela s’ajoute, l’étendue de leurs fonctions qui comprend désormais l’analyse prédictive des données. Cependant, ce pôle stratégique est souvent confronté à des défis tels que le difficile accès à la donnée ou la faible automatisation des tâches.
La Data Virtualization ou virtualisation des données permet d’accroître la valeur ajoutée de la fonction finance et il s’agit d’un levier qui permet de consacrer le plus du temps à l'analyse prédictive au détriment de la collecte et la consolidation depuis les différentes sources de données. Visionnez ce webinar pour découvrir comment la Data Virtualization permet de :
- Donner plus d'autonomie à la finance vis-à-vis de l'informatique, tant sur la modification des paramétrages, que sur la modélisation des règles de gestion, sur les éditions …
- Éviter la saisie multiple d'informations, de nombreux retraitements manuels, et procéder à différentes simulations.
- Effectuer des analyses multidimensionnelles
- Passer plus de temps sur les tâches à valeur ajoutée
- Utiliser, dans un seul outil, les données en provenance de plusieurs sources
- Se concentrer sur l’analyse plutôt que sur la consolidation des données
- Garantir la rigueur du reporting institutionnel
… et bien plus encore ! La séance comprend une démo live de cette technologie appliquée à l’analyse prédictive.
More Related Content
What's hot
From Knowledge Graphs to AI-powered SEO: Using taxonomies, schemas and knowle...
From Knowledge Graphs to AI-powered SEO: Using taxonomies, schemas and knowle...Connected Data World
Do you want to learn how to use the low-hanging fruit of knowledge graphs — schema.org and JSON-LD — to annotate content and improve your SEO with semantics and entities? This hands-on workshop with one of the leading Semantic SEO practitioners will help you get started.Graph-based intelligence analysis
For decades, the intelligence community has been collecting and analyzing information to produce timely and actionable insights for intelligence consumers. But as the amount of information collected increases, analysts are facing new challenges in terms of data processing and analysis. In this presentation, we explore the possibilities that graph technology is offering for intelligence analysis.
Knowledge Graphs Webinar- 11/7/2017
A webinar on how Neo4j customers like Nasa, AirBnB, eBay, government agencies, investigative journalists and others are building Knowledge Graphs to inform today and tomorrow’s solutions.
Combining a Knowledge Graph and Graph Algorithms to Find Hidden Skills at NASA
Speaker: David Meza, Sr. Data Scientist, NASA
Enterprise Knowledge Graph
by Lukas Masuch, Henning Muszynski and Benjamin Raethlein
The Enterprise Knowledge Graph is a disruptive platform that combines emerging Big Data and Graph technologies to reinvent knowledge management inside organizations. This platform aims to organize and distribute the organization’s knowledge, and making it centralized and universally accessible to every employee. The Enterprise Knowledge Graph is a central place to structure, simplify and connect the knowledge of an organization. By removing complexity, the knowledge graph brings more transparency, openness and simplicity into organizations. That leads to democratized communications and empowers individuals to share knowledge and to make decisions based on comprehensive knowledge. This platform can change the way we work, challenge the traditional hierarchical approach to get work done and help to unleash human potential!
Using graph technology for multi-INT investigations
Learn how to break silos and reduce complexity in Multi-INT investigations with graphs.
Graphs in Telecommunications - Jesus Barrasa, Neo4j
Graphs in Telecommunications
Jesús Barrasa, Neo4j
Big Data Fabric 2.0 Drives Data Democratization
In their webinar "Big Data Fabric 2.0 Drives Data Democratization" Ben Szekley, Cambridge Semantics’ SVP of Field Operations, and guest speaker, Forrester’s Noel Yuhanna, author of the Forrester report: “Big Data Fabric 2.0 Drives Data Democratization”, explored why data-driven businesses are making a big data fabric part of their data strategy to minimize data complexity, integrate siloed data, deliver real-time trusted insights, and to create new business opportunities. These are the slides from that webinar.
Big Data Landscape 2016
Annual Big Data Landscape prepared by FIrstMark. Check out full blog post: "Is Big Data Still a Thing"? at http://mattturck.com/2016/02/01/big-data-landscape/
Using a Semantic and Graph-based Data Catalog in a Modern Data Fabric
Watch this webinar to learn about the benefits of using semantic and graph database technology to create a Data Catalog of all of an enterprise's data, regardless of source or format, as part of a modern IT or data management stack and an important step toward building an Enterprise Data Fabric.
How Semantics Solves Big Data Challenges
Today, organizations want both IT simplicity and innovation, but reliance on traditional databases only leads to more complexity, longer development cycles, and more silos. In fact, organizations report that the #1 impediment to big data success is having too many silos. In this webinar, we will discuss how a new database technology, semantics, solves this problem by providing a new approach to modeling data that focuses on relationships and context, making it easier for data to be understood, searched, and shared. With semantics, world-leading organizations are integrating disparate data faster and easier and building smarter applications with richer analytic capabilities—benefits that we look forward to diving into during the webinar.
Linking SharePoint Documents with Structured Data
Unified views of business-critical information across all customer-facing processes and HR-related tasks are most relevant for decision makers.
In this talk we present a SharePoint extension that supports the automatic linking of unstructured content like Word documents with structured information from other databases, such as statistical data. As a result, decision makers have knowledge portals based on linked data at their fingertips.
While the importance of managed metadata and Term Store is clear to most SharePoint architects, the significance of a semantic layer outside of the content silos has not yet been explored systematically.
We will present a four-layered content architecture and will take a close look on some of the aspects of the semantic layer and its integration with SharePoint:
- Keeping Term Store and the semantic layer in sync
- Automatic tagging of SharePoint content
- Use of graph databases to store tags
- Entity-centric search & analytics applications
Metadata is most often stored per data source, and therefore it is meaningless outside of the silo. In this presentation, we will give a live demo of a SharePoint extension that makes use of an explicit semantic layer based on standards. This approach builds the basis to start linking data across the silos in a most agile way.
The resulting knowledge graph can start on a small scale, to develop continuously and to grow with the requirements. In this presentation we will give an example to illustrate how initially disconnected HR-related data (CVs in SharePoint; statistical data from labour market; skills and competencies taxonomies; salary spreadsheets) gets linked automatically, and is then made available through an extensive search & analytics application.
Risk Analytics Using Knowledge Graphs / FIBO with Deep Learning
This EDM Council webinar, sponsored by Cambridge Semantics Inc. and featuring FI Consulting, explores the challenges common to a risk analytics pipeline, application of graph analytics to mortgage loan data and use cases in adjacent areas including customer service, collections, fraud and AML.
NoSQL Technology and Real-time, Accurate Predictive Analytics
Big Data: NoSQL Technology and Real-time, Accurate Predictive Analytics
Enjoy this insightful webinar moderated by Matt Aslett, Research Director at 451 Group beginning with a brief overview of Objectivity, Inc. and its products Objectivity/DB, a world class object database and InfiniteGraph, the enterprise proven, scalable and distributed graph database with deployments across multiple major verticals including government, telecom, finance, security, and social networking. Learn how Georgetown University is taking advantage of Objectivity’s products to develop one of the most interconnected databases today. Examining information from all types of sources worldwide in real-time.
J.C. Smart, Director Global Insight Laboratory, Georgetown University- Coming Soon
Leon Guzenda, Founder, Objectivity – a founding member of Objectivity, Inc. in 1988, one of the original architects of Objectivity/DB and Chief Technology Officer. He now consults with the company and works with Objectivity’s Big Data and Analytics customers/partners to deploy Objectivity/DB and InfiniteGraph, a high performance, scalable graph database.
Matt Aslett, Research Director, 451 Group – As Research Director for data management and analytics within 451 Research’s Information Management practice, Matt has overall responsibility for the coverage of operational and analytic databases, data integration, data quality, and business intelligence. Matt’s own primary area of focus is on relational and non-relational databases, data warehousing, data caching, and Hadoop. Matthew is also an expert in open source software and regularly contributes to 451 Research’s open source-related research.
Graph technology and data-journalism: the case of the Paradise Papers
Discover how graph analysis and visualization technologies allowed the ICIJ journalists to highlight the suspicious relations between political figures and offshore companies in the Paradise Papers investigations.
From Taxonomies and Schemas to Knowledge Graphs: Parts 1 & 2
Do you have experience in data modeling, or using taxonomies to classify things, and want to upgrade to modeling knowledge graphs? This hands-on workshop with one of the leading knowledge graph practitioners will help you get started.
Parts 1 & 2
BrightTALK - Semantic AI
Bringing Machine Learning and Knowledge Graphs Together
Six Core Aspects of Semantic AI:
- Hybrid Approach
- Data Quality
- Data as a Service
- Structured Data Meets Text
- No Black-box
- Towards Self-optimizing Machines
Leveraging Knowledge Graphs in your Enterprise Knowledge Management System
Knowledge graphs and graph-based data in general are becoming increasingly important for addressing various data management challenges in industries such as financial services, life sciences, healthcare or energy.
At the core of this challenge is the comprehensive management of graph-based data, ranging from taxonomy to ontology management to the administration of comprehensive data graphs along with a defined governance framework. Various data sources are integrated and linked (semi) automatically using NLP and machine learning algorithms. Tools for securing high data quality and consistency are an integral part of such a platform.
PoolParty 7.0 can now handle a full range of enterprise data management tasks. Based on agile data integration, machine learning and text mining, or ontology-based data analysis, applications are developed that allow knowledge workers, marketers, analysts or researchers a comprehensive and in-depth view of previously unlinked data assets.
At the heart of the new release is the PoolParty GraphEditor, which complements the Taxonomy, Thesaurus, and Ontology Manager components that have been around for some time. All in all, data engineers and subject matter experts can now administrate and analyze enterprise-wide and heterogeneous data stocks with comfortable means, or link them with the help of artificial intelligence.
What's hot (20)
From Knowledge Graphs to AI-powered SEO: Using taxonomies, schemas and knowle...
From Knowledge Graphs to AI-powered SEO: Using taxonomies, schemas and knowle...
Combining a Knowledge Graph and Graph Algorithms to Find Hidden Skills at NASA
Combining a Knowledge Graph and Graph Algorithms to Find Hidden Skills at NASA
Using graph technology for multi-INT investigations
Using graph technology for multi-INT investigations
Graphs in Telecommunications - Jesus Barrasa, Neo4j
Graphs in Telecommunications - Jesus Barrasa, Neo4j
Using a Semantic and Graph-based Data Catalog in a Modern Data Fabric
Using a Semantic and Graph-based Data Catalog in a Modern Data Fabric
Risk Analytics Using Knowledge Graphs / FIBO with Deep Learning
Risk Analytics Using Knowledge Graphs / FIBO with Deep Learning
NoSQL Technology and Real-time, Accurate Predictive Analytics
NoSQL Technology and Real-time, Accurate Predictive Analytics
Graph technology and data-journalism: the case of the Paradise Papers
Graph technology and data-journalism: the case of the Paradise Papers
From Taxonomies and Schemas to Knowledge Graphs: Parts 1 & 2
From Taxonomies and Schemas to Knowledge Graphs: Parts 1 & 2
Leveraging Knowledge Graphs in your Enterprise Knowledge Management System
Leveraging Knowledge Graphs in your Enterprise Knowledge Management System
Similar to Visualize the Knowledge Graph and Unleash Your Data
Graph Databases – Benefits and Risks
Graph databases provide the ability to quickly discover and integrate key relationships between enterprise data sets. Business use cases such as recommendation engines, social networks, enterprise knowledge graphs, and more provide valuable ways to leverage graph databases in your organization. This webinar will provide an overview of graph database technologies, and how they can be used for practical applications to drive business value.
Impulser la digitalisation et modernisation de la fonction Finance grâce à la...
Voir: https://bit.ly/2Oycfnn
À l’ère du numérique, la digitalisation et modernisation des services financiers sont plus que jamais requises compte tenu de leur rôle clé dans les processus de prise de décisions et le pilotage de la performance. Les directions financières nécessitent ainsi de fournir des informations fiables et vérifiées, tout en répondant aux exigences de gouvernance et de sécurité. À cela s’ajoute, l’étendue de leurs fonctions qui comprend désormais l’analyse prédictive des données. Cependant, ce pôle stratégique est souvent confronté à des défis tels que le difficile accès à la donnée ou la faible automatisation des tâches.
La Data Virtualization ou virtualisation des données permet d’accroître la valeur ajoutée de la fonction finance et il s’agit d’un levier qui permet de consacrer le plus du temps à l'analyse prédictive au détriment de la collecte et la consolidation depuis les différentes sources de données. Visionnez ce webinar pour découvrir comment la Data Virtualization permet de :
- Donner plus d'autonomie à la finance vis-à-vis de l'informatique, tant sur la modification des paramétrages, que sur la modélisation des règles de gestion, sur les éditions …
- Éviter la saisie multiple d'informations, de nombreux retraitements manuels, et procéder à différentes simulations.
- Effectuer des analyses multidimensionnelles
- Passer plus de temps sur les tâches à valeur ajoutée
- Utiliser, dans un seul outil, les données en provenance de plusieurs sources
- Se concentrer sur l’analyse plutôt que sur la consolidation des données
- Garantir la rigueur du reporting institutionnel
… et bien plus encore ! La séance comprend une démo live de cette technologie appliquée à l’analyse prédictive.
Modernizing Integration with Data Virtualization
Watch full webinar here: https://bit.ly/3CMqS0E
Today, businesses have more data and data types combined with more complex ecosystems than they have ever had before. Examples include on-premise data marts, data warehouses, data lakes, applications, spreadsheets, IoT data, sensor data, unstructured, etc. combined with cloud data ecosystems like Snowflake, Big Query, Azure Synapse, Amazon S3, Redshift, Databricks, SaaS apps, such as Salesforce, Oracle, Service Now, Workday, and on and on.
Data, Analytics, Data Science and Architecture teams are struggling to provide the business users with the right data as quickly and efficiently as possible to quickly enable Analytics, Dashboards, BI, Reports, etc. Unfortunately, many enterprises seek to meet this pressing need by utilizing antiquated and legacy 40+ year-old approaches. There is a better way. Proven by thousands of other companies.
As Forrester so astutely reported in their recent Total Economic Impact Study, companies who employed Data Virtualization reported a “65% decrease in data delivery times over ETL” and an “83% reduction in time to new revenue.”
Join us for this very educational webinar to learn firsthand from Denodo Technologies and Fusion Alliance how:
- Data Virtualization helps your company save time and money by eliminating superfluous ETL pipelines and data replication.
- Data Virtualization can become the cornerstone of your modern data approach to deliver data faster and more efficiently than old legacy approaches at enterprise scale.
- How quickly and easily, Data Virtualization can scale, even in the most complex environments, to create a universal abstraction semantic model(s) for all of your cloud, on premise, structured, unstructured and hybrid data
- Data Mesh and Data Fabric architecture patterns for maximum reuse
- Other customers have used, and are using, Data Virtualization to tackle their toughest data integration and data delivery challenges
- Fusion Alliance can help you define a data strategy tailored to your organization’s needs and requirements, and how they can help you achieve success and enable your business with self-service capabilities
Case Study - Gordon Foods Delivers Fresh Data to the Cloud
The traditional ETL approach for moving data to the cloud is labor-intensive and costly, not to mention brittle and slow, draining organizations of time and resources that they just do not have.
In this webinar, you will hear from Gordon Food Service and how they sharpened their competitive edge by delivering the freshest data to Google Cloud and dished up a better customer experience through real-time data insights. You will discover how Qlik’s data integration platform enabled Gordon Food Service to successfully run their Data Modernization Analytics Program and build real-time analytic data pipelines, unlocking multiple data sources, to Google Cloud with simple yet powerful data delivery.
Register today and learn how Gordon Foods:
• Improved their Customer Experience
• Replaced slow custom replication scripts and speed up analytics
• Simplify and automate their real-time data streaming process
• Moves thousands of objects on a daily basis
Find out how your organization can breathe new life into your data in the cloud, stay ahead of changing demands while lowering over-reliance on resources, production time and costs.
Data Virtualization: An Introduction
Watch full webinar here: https://bit.ly/2vN59VK
What started to evolve as the most agile and real-time enterprise data fabric, data virtualization is proving to go beyond its initial promise and is becoming one of the most important enterprise big data fabrics.
Attend this session to learn:
- What data virtualization really is.
- How it differs from other enterprise data integration technologies.
- Why data virtualization is finding enterprise-wide deployment inside some of the largest organizations.
Business Centric Data Modeling
Business-centric data models are key to gaining a clear view of the data that drives the business – from customers to products to invoices and more. They offer a clear, visual way for both business and technical stakeholders to communicate around the crucial business rules and definitions that drive both operational usage of data as well as analytics and reporting. This webinar will provide practical, concrete steps in creating valuable, business-centric data models that can show immediate value to the organization, while at the same time building towards a full-enterprise view.
BI, Hive or Big Data Analytics?
As more organizations look to Hadoop as the technology solution for big data analytics, common questions arise.
Join us in this case study look at an online services provider's experience with Big Data and how they answered the questions:
*What does big data analytics do that my existing BI software doesn’t?
*Will Hadoop replace my data warehouse?
*What about Hive?
BAR360 open data platform presentation at DAMA, Sydney
BAR360 open data platform presentation at DAMA, Sydney August 2015
Get Started with the Most Advanced Edition Yet of Neo4j Graph Data Science
Get Started with the Most Advanced Edition Yet of Neo4j Graph Data Science
Self Service Analytics and a Modern Data Architecture with Data Virtualizatio...
Watch full webinar here: https://bit.ly/32TT2Uu
Data virtualization is not just for self-service, it’s also a first-class citizen when it comes to modern data platform architectures. Technology has forced many businesses to rethink their delivery models. Startups emerged, leveraging the internet and mobile technology to better meet customer needs (like Amazon and Lyft), disrupting entire categories of business, and grew to dominate their categories.
Schedule a complimentary Data Virtualization Discovery Session with g2o.
Traditional companies are still struggling to meet rising customer expectations. During this webinar with the experts from g2o and Denodo we covered the following:
- How modern data platforms enable businesses to address these new customer expectation
- How you can drive value from your investment in a data platform now
- How you can use data virtualization to enable multi-cloud strategies
Leveraging the strategy insights of g2o and the power of the Denodo platform, companies do not need to undergo the costly removal and replacement of legacy systems to modernize their systems. g2o and Denodo can provide a strategy to create a modern data architecture within a company’s existing infrastructure.
Spark: Building an application from Start to Finish
Slides from August 2017 STLHUG User Group. Adam Doyle discussed GDPR and building Spark applications..
Course 8 : How to start your big data project by Eric Rodriguez
For more info about our Big Data courses, check out our website ➡️ https://www.betacowork.com/big-data/
---------
"Data is the new oil" - Many companies and professionals do not know how to use their data or are not aware of the added value they could gain from it.
It is in response to these problems that the project “Brussels: The Beating Heart of Big Data” was born.
This project, financed by the Region of Brussels Capital and organised by Betacowork, offers 3 training cycles of 10 courses on big data, at both beginner and advanced levels. These 3 cycles will be followed by a Hackathon weekend.
No prerequisites are required to start these courses. The aim of these courses is to familiarize participants with the principles of Big Data.
------
For more info about our Big Data courses, check out our website ➡️ https://www.betacowork.com/big-data/
IBM Cloud pak for data brochure
IBM Cloud Pak for Data is a single unified platform which helps to unify and simplify the collection, organization and analysis of data. Enterprises can turn data into insights through an integrated cloud-native architecture. IBM Cloud Pak for Data is extensible, easily customized to unique client data and AI landscapes through an integrated catalog of IBM, open source and third-party microservices add-ons
Organising the Data Lake - Information Management in a Big Data World
Organising the Data Lake - Information Management in a Big Data World
Microsoft Fabric & Profisee MDM Are Better Together
Learn how Microsoft Fabric will help modern organizations unlock the power of their data and lay the foundation for the era of AI — directly from experts at Microsoft and Profisee. Watch the full webinar recording here: https://profisee.com/event/better-together-profisee-mdm-microsoft-fabric/
Building the Artificially Intelligent Enterprise
This session looks at where we are today with data and analytics and what is needed to transition to the Artificially Intelligent Enterprise.
How do you mobilise developers to exploit what data scientists and business analysts have built? How do you align it all with business strategy to maximise business outcomes? How do you combine BI, predictive and prescriptive analytics, automation and reinforcement learning to get maximum value across the enterprise? What is the blueprint for building the artificially intelligent enterprise?
•Data and analytics – Where are we?
•Why is the journey only half-way done?
•2021 and beyond – The new era of AI usage and not just build
•The requirement – event-driven, on-demand and automated analytics
•Operationalising what you build – DataOps, MLOps and RPA
•Mobilising the masses to integrate AI into processes – what needs to be done?
•Business strategy alignment – the guiding light to AI utilisation for high reward
•Agility step change – the shift to no-code integration of AI by citizen developers
•Recording decisions, and analysing business impact
•Reinforcement-learning – transitioning to continuous reward
The New Database Frontier: Harnessing the Cloud
The Briefing Room with Rick Sherman and MarkLogic
Live Webcast on May 13, 2014
Watch the archive:
https://bloorgroup.webex.com/bloorgroup/lsr.php?RCID=9cd8eec52f7968721fdcd922e4f70369
The number of data types and sources is increasing almost daily anymore, which poses serious challenges for analytics and discovery. With many of these data sets in the Cloud, analysts are realizing that merging such public resources with internal information assets can be quite problematic. Solutions like virtualization and federation can get the job done, but another option is to employ a database that can natively connect to all these external sources.
Register for this episode of The Briefing Room to hear veteran Analyst Rick Sherman as he explains how the changing needs of the user are driving database innovation. He’ll be briefed by Ken Krupa of MarkLogic, who will tout his company’s NoSQL document database. He’ll discuss the importance of expanding the definition of what it means to be a database, and he’ll show how MarkLogic’s ability to tap into more sources than ever creates a scale-out data nerve center, thus delivering faster and better insights.
Visit InsideAnlaysis.com for more information.
Similar to Visualize the Knowledge Graph and Unleash Your Data (20)
Impulser la digitalisation et modernisation de la fonction Finance grâce à la...
Impulser la digitalisation et modernisation de la fonction Finance grâce à la...
Case Study - Gordon Foods Delivers Fresh Data to the Cloud
Case Study - Gordon Foods Delivers Fresh Data to the Cloud
BAR360 open data platform presentation at DAMA, Sydney
BAR360 open data platform presentation at DAMA, Sydney
Get Started with the Most Advanced Edition Yet of Neo4j Graph Data Science
Get Started with the Most Advanced Edition Yet of Neo4j Graph Data Science
Self Service Analytics and a Modern Data Architecture with Data Virtualizatio...
Self Service Analytics and a Modern Data Architecture with Data Virtualizatio...
Spark: Building an application from Start to Finish
Spark: Building an application from Start to Finish
Course 8 : How to start your big data project by Eric Rodriguez
Course 8 : How to start your big data project by Eric Rodriguez
Organising the Data Lake - Information Management in a Big Data World
Organising the Data Lake - Information Management in a Big Data World
zData BI & Advanced Analytics Platform + 8 Week Pilot Programs
zData BI & Advanced Analytics Platform + 8 Week Pilot Programs
Microsoft Fabric & Profisee MDM Are Better Together
Microsoft Fabric & Profisee MDM Are Better Together
More from Linkurious
Webinar: What's new in Linkurious Enterprise 2.8
With Linkurious Enterprise 2.8, we focused on time filtering with a Timeline and on providing more control on data entry and data presentation with support for data schema.
We discuss:
- The benefits of a schema and how to set it up.
- How to explore and filter the graph over time using the Timeline.
- How to disable the auto-save mode.
We also discuss the changes in the graph layout menu.
What's new in Linkurious Enterprise 2.7
The slides from a presentation of Linkurious Enterprise, in which we look at what’s new in this release, including the new Query Template capabilities and the redesign of the query panel.
Video of the presentation: https://youtu.be/ucuntmqzTYI
GraphTech Ecosystem - part 3: Graph Visualization
The graph ecosystem presentation lists and introduces the graph visualization actors: graph visualization libraries and toolkits; graph visualizers and add-ons
GraphTech Ecosystem - part 2: Graph Analytics
The graph ecosystem presentation lists and introduces a vast majority of graph analytics actors: graph analytics frameworks; graph processing engines; graph analytics libraries and toolkits; graph query languages and projects.
GraphTech Ecosystem - part 1: Graph Databases
The graph ecosystem presentation lists and introduces a vast majority of storage systems for graph-like data: native graph databases, RDF databases, multi-model systems or systems with a graph API.
3 types of fraud graph analytics can help defeat
Organizations across industries are adopting graph analytics to reinforce their anti-fraud programs. In this presentation, we examine three types of fraud graph analytics can help investigators combat. Blog post: https://linkurio.us/blog/3-fraud-graph-analytics-help-defeat/
Graph analytics in Linkurious Enterprise
Graph algorithms provide tools to extract insights from graph data. From detecting anomalies to understanding what are the key elements in a network or finding communities, graph algorithms reveal information that would otherwise remain hidden. Learn about:
- The most popular graph algorithms and what they can be used for;
- The benefits of using graph analytics with Linkurious Enterprise;
- How to integrate graph analytics in Linkurious Enterprise.
Fraudes Financières: Méthodes de Prévention et Détection
Cette présentation en partenariat avec DataStax revient sur comment détecter en temps réel des activités frauduleuses telles que la fraude identitaire. Des applications concrètes de ces technologies seront détaillées, de l’affaire des Panama Papers à des cas d’usages quotidiens dans des banques et des institutions financières. Les techniques de lutte antifraude ainsi que les avantages des approches orientées graphe seront également présentés.
Detecting eCommerce Fraud with Neo4j and Linkurious
Last year, the global eCommerce market represented $1.9 trillions. As the market expands worldwide, the opportunity for fraud keeps growing with fraudsters constantly refining their tactics to outsmart anti-fraud frameworks. From chargeback fraud to re-shipping scam or identity fraud, numerous types of fraud can impact your organization. While collecting data is essential to enable real-time risk assessment, many organizations don’t have the necessary tools to find the insights needed to block fraud attempts.
Neo4j and Linkurious offer a solution to tackle the eCommerce fraud challenge. Their combined technologies provide a 360° overview of organization’s data and allow real-time analysis and detection of eCommerce fraud patterns and activities.
Graph-powered data lineage in Finance
Slides of Linkurious presentation at GraphConnect London 2017.
Tracking the flow of data is the foundation for solid data governance. It's also a compliance imperative for financial institutions impacted by BCBS 239. In this talk, we will discuss how graph-oriented data lineage is well suited for today's growing data volume and complexity. You will learn how to answer questions like: What would be the impact of a component of my data pipeline breaking up? Where does the data from a particular report originate?
Linkurious SDK: Build enterprise-ready graph applications faster
Graph technologies have the potential to help businesses understand complex connected data. From financial crime to cyber-security to IT management, specific business requires custom applications. This is why we created the Linkurious SDK , a toolkit that enables you to quickly build secure and flexible applications to leverage the connections within your data or unveil hidden relationships.
Discover in this presentation the challenges of integrating graph technologies into enterprise applications; and how to use the Linkurious SDK to build a robust, secure and interactive graph application.
Fighting financial crime with graph analysis at BIWA Summit 2017
Additional details on our blog: https://linkurio.us/visualize-oracle-graph-data-ogma-library/
Discover how to use graph analysis to identify suspicious connections and unmask criminals. In this session, Jean will share his experience working on the Panama Papers or with banks and insurance companies (first-party fraud, anti-money laundering, insurance fraud). He will explain how to combine the kind of graph analytics enabled by Oracle Spatial and Graph with powerful graph visualization to help analysts detect, investigate and stop financial crime.
Reinforcing AML systems with graph technologies.
Anti-money laundering (AML) has become complex and costly for institutions and enterprises. Nowadays, to thwart criminal intricate strategies, financial crime units have to gather, monitor and investigate large amounts of connected data.
Graph analysis and visualization technologies can provide an holistic view of the various entities and their relationships to unveil wrongdoings.
Anti-money laundering (AML) has become complex and costly for institutions and enterprises. Graph analysis and visualization technologies like Linkurious are a great fit to help AML analysts fight money laundering.
Discover in this presentation how to automate the monitoring of high risk customers with patterns alerts and how to assess risk-levels by visually investigating suspicious cases.
More information on www.linkurio.us
Using graphs technologies for intelligence analysis.
Discover how to use graph patterns to detect terrorist threats and how to investigate suspicious networks with graph visualization in Linkurious.
The 8 most common graph visualization mistakes
Are you making these 8 mistakes in your graph visualizations?
Panama papers: how ICIJ used Linkurious to investigate the Mossack Fonseca leaks
Discover how ICIJ used Linkurious to investigate the Mossack Fonseca leaks. Presentation at the GFII Dixit conference.
La visualisation au service de la lutte contre la fraude
La visualisation de graphes de Linkurious et les bases de données Neo4j permettent de renforcer les systèmes de lutte contre la fraude.
Finding answers through visualization (GraphDay Barcelona Feb 2016)
Presentation of Linkurious graph visualization software.
Graph analysis of the European public tenders
Let's explore open data about European public contracts with Linkurious and Neo4j.
Using graph technologies to fight fraud
Learn how to use graph technologies to fight fraud. Combine the power of the Neo4j graph database with an easy to use graph visualization tool.
More from Linkurious (20)
Fraudes Financières: Méthodes de Prévention et Détection
Fraudes Financières: Méthodes de Prévention et Détection
Detecting eCommerce Fraud with Neo4j and Linkurious
Detecting eCommerce Fraud with Neo4j and Linkurious
Linkurious SDK: Build enterprise-ready graph applications faster
Linkurious SDK: Build enterprise-ready graph applications faster
Fighting financial crime with graph analysis at BIWA Summit 2017
Fighting financial crime with graph analysis at BIWA Summit 2017
Using graphs technologies for intelligence analysis.
Using graphs technologies for intelligence analysis.
Panama papers: how ICIJ used Linkurious to investigate the Mossack Fonseca leaks
Panama papers: how ICIJ used Linkurious to investigate the Mossack Fonseca leaks
La visualisation au service de la lutte contre la fraude
La visualisation au service de la lutte contre la fraude
Finding answers through visualization (GraphDay Barcelona Feb 2016)
Finding answers through visualization (GraphDay Barcelona Feb 2016)
Recently uploaded
Generative AI Deep Dive: Advancing from Proof of Concept to Production
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf
FIDO Alliance Osaka Seminar
Elizabeth Buie - Older adults: Are we really designing for our future selves?
Elizabeth Buie - Older adults: Are we really designing for our future selves?
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
UiPath Community Day Dubai: AI at Work..
Welcome to the first live UiPath Community Day Dubai! Join us for this unique occasion to meet our local and global UiPath Community and leaders. You will get a full view of the MEA region's automation landscape and the AI Powered automation technology capabilities of UiPath. Also, hosted by our local partners Marc Ellis, you will enjoy a half-day packed with industry insights and automation peers networking.
📕 Curious on our agenda? Wait no more!
10:00 Welcome note - UiPath Community in Dubai
Lovely Sinha, UiPath Community Chapter Leader, UiPath MVPx3, Hyper-automation Consultant, First Abu Dhabi Bank
10:20 A UiPath cross-region MEA overview
Ashraf El Zarka, VP and Managing Director MEA, UiPath
10:35: Customer Success Journey
Deepthi Deepak, Head of Intelligent Automation CoE, First Abu Dhabi Bank
11:15 The UiPath approach to GenAI with our three principles: improve accuracy, supercharge productivity, and automate more
Boris Krumrey, Global VP, Automation Innovation, UiPath
12:15 To discover how Marc Ellis leverages tech-driven solutions in recruitment and managed services.
Brendan Lingam, Director of Sales and Business Development, Marc Ellis
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
The Metaverse and AI: how can decision-makers harness the Metaverse for their...
The Metaverse is popularized in science fiction, and now it is becoming closer to being a part of our daily lives through the use of social media and shopping companies. How can businesses survive in a world where Artificial Intelligence is becoming the present as well as the future of technology, and how does the Metaverse fit into business strategy when futurist ideas are developing into reality at accelerated rates? How do we do this when our data isn't up to scratch? How can we move towards success with our data so we are set up for the Metaverse when it arrives?
How can you help your company evolve, adapt, and succeed using Artificial Intelligence and the Metaverse to stay ahead of the competition? What are the potential issues, complications, and benefits that these technologies could bring to us and our organizations? In this session, Jen Stirrup will explain how to start thinking about these technologies as an organisation.
Climate Impact of Software Testing at Nordic Testing Days
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Elevating Tactical DDD Patterns Through Object Calisthenics
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdf
Building better applications for business users with SAP Fiori.
• What is SAP Fiori and why it matters to you
• How a better user experience drives measurable business benefits
• How to get started with SAP Fiori today
• How SAP Fiori elements accelerates application development
• How SAP Build Code includes SAP Fiori tools and other generative artificial intelligence capabilities
• How SAP Fiori paves the way for using AI in SAP apps
Securing your Kubernetes cluster_ a step-by-step guide to success !
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
State of ICS and IoT Cyber Threat Landscape Report 2024 preview
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Removing Uninteresting Bytes in Software Fuzzing
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
DevOps and Testing slides at DASA Connect
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
PHP Frameworks: I want to break free (IPC Berlin 2024)
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Recently uploaded (20)
Generative AI Deep Dive: Advancing from Proof of Concept to Production
Generative AI Deep Dive: Advancing from Proof of Concept to Production
FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf
FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf
Elizabeth Buie - Older adults: Are we really designing for our future selves?
Elizabeth Buie - Older adults: Are we really designing for our future selves?
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf
The Metaverse and AI: how can decision-makers harness the Metaverse for their...
The Metaverse and AI: how can decision-makers harness the Metaverse for their...
Climate Impact of Software Testing at Nordic Testing Days
Climate Impact of Software Testing at Nordic Testing Days
Elevating Tactical DDD Patterns Through Object Calisthenics
Elevating Tactical DDD Patterns Through Object Calisthenics
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdf
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdf
Securing your Kubernetes cluster_ a step-by-step guide to success !
Securing your Kubernetes cluster_ a step-by-step guide to success !
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
State of ICS and IoT Cyber Threat Landscape Report 2024 preview
State of ICS and IoT Cyber Threat Landscape Report 2024 preview
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
Transcript: Selling digital books in 2024: Insights from industry leaders - T...
Transcript: Selling digital books in 2024: Insights from industry leaders - T...
PHP Frameworks: I want to break free (IPC Berlin 2024)
PHP Frameworks: I want to break free (IPC Berlin 2024)
Free Complete Python - A step towards Data Science
Free Complete Python - A step towards Data Science
Visualize the Knowledge Graph and Unleash Your Data
- 1. Stardog and Linkurious Visualize the Knowledge Graph and Unleash Your Data
- 2. WEBINAR AGENDA 1. Introductions 2. Company Overviews 3. Data Silos 4. Knowledge Graph 5. Visualizations 6. Q&A/Conclusion
- 3. INTRODUCTIONS Bryan Prout, Senior Director Customer Success, Stardog Jean Villedieu, Co-Founder, Linkurious Mike Grove, Co-Founder & VP of Engineering, Stardog
- 4. THE ENTERPRISE KNOWLEDGE GRAPH PLATFORM
- 6. Data Silos
- 8. ENTERPRISES STRUGGLE WITH DATA SILOS
- 9. UNCONNECTED DATA BECOMES A LIABILITY How can an enterprise query all this data as a single unified data source? UNIFIED DATA MODEL RDB RDB RDF
- 10. Knowledge Graph
- 11. ENTERPRISES STILL THINK IN TREES AND TABLES
- 12. GRAPHS ARE EVERYWHERE Open Graph Knowledge Graph
- 13. ENTERPRISE KNOWLEDGE GRAPH POSTGRES CSV MONGO PDF ORACLE DB2 MARKLOGIC HDFS
- 14. STARDOG IN THE ENTERPRISE
- 15. KNOWLEDGE TOOLKIT • Virtual graphs • Logical data model • Integrity constraints • Integrated machine learning • Full-text, spatial indexes • Entity extraction, linking • NLP friendly
- 18. LINKURIOUS ENTERPRISE • Intuitive interface to SEARCH AND VISUALIZE connected data • Turn key INTEGRATION with Stardog • FASTER investigations, DISCOVERY of new insights
- 19. ARCHITECTURE OVERVIEW Linkurious INVESTIGATION & DISCOVERY
- 20. Financial crime: banks, insurance companies or tax agencies are using Linkurious Enterprise to fight money-laundering, fraud or tax evasion. KNOWLEDGE GRAPH USE CASES Cyber-security: cyber analysts are using Linkurious to detect and investigate threats. Security: law enforcement and government agencies are using Linkurious Enterprise to fight terrorism and criminal networks. Medical research: medical researchers are using Linkurious Enterprise to develop new drugs.
- 23. Q&A SESSION
- 25. THANK YOU!