This webinar focuses on the particular use case of graph databases in Network & IT-Management. This webinar is designed for people who work with Network Management at telecom companies or professionals within industries that handle and rely on complex networks.
We’ll start with an overview of Neo4j and Graph-thinking within Networks, explaining how Neworks are naturally modelled as graphs. We’ll explain how graph databases vastly help mitigate some of the major challenges the Network and Security Managers face on daily basis — including intrusions and other cyber crimes, performance optimization, outage simulations, fraud prevention and more.
The year of the graph: do you really need a graph database? How do you choose...George Anadiotis
Graph databases have been around for more than 15 years, but it was AWS and Microsoft getting in the domain that attracted widespread interest. If they are into this, there must be a reason.
Everyone wants to know more, few can really keep up and provide answers. And as this hitherto niche domain is in the mainstream now, the dynamics are changing dramatically. Besides new entries, existing players keep evolving.
I’ve done the hard work of evaluating solutions, so you don’t have to. An overview of the domain and selection methodology, as presented in Big Data Spain 2018
While the Rio 2016 Olympics are winding down and the final medals are being handed out, we thought we would share a bit of work that was done recently by Rik Van Bruggen to explore a really interesting dataset in Neo4j.
Based on an original public dataset by the UK newspaper The Guardian, Rik completed the medallist dataset to contain over 30,000 Olympians between 1896 and 2012. He created a graph model, loaded the data, and wrote a bunch of example queries that yielded some very interesting results. Join us for this 30 minute webinar where we’ll take you through this great Olympian graph and take the data for a spin yourself afterwards.
Congratulations, your data is up and running in a graph database! This is the first step of many to unlocking the potential in your data. It’s easy to get mired in the complexities of graph technology and forget that real users, mere mortals, will need to use this information to inform mission critical tasks. To get the value out of your graph investment, you’ll need to provide an experience that enables users to explore and visualize your graph data in meaningful ways.
In this talk, we’ll take a hands on approach to applying user-centered strategies and leveraging the latest UI tools to rapidly create great experiences with graph data. Topics will include network analysis queries with Cypher and APOC, tailoring experiences to the intended audience and data, determining the the right visualization for the job and cutting through the clutter on choosing the right visualization tools.
This webinar focuses on the particular use case of graph databases in Network & IT-Management. This webinar is designed for people who work with Network Management at telecom companies or professionals within industries that handle and rely on complex networks.
We’ll start with an overview of Neo4j and Graph-thinking within Networks, explaining how Neworks are naturally modelled as graphs. We’ll explain how graph databases vastly help mitigate some of the major challenges the Network and Security Managers face on daily basis — including intrusions and other cyber crimes, performance optimization, outage simulations, fraud prevention and more.
The year of the graph: do you really need a graph database? How do you choose...George Anadiotis
Graph databases have been around for more than 15 years, but it was AWS and Microsoft getting in the domain that attracted widespread interest. If they are into this, there must be a reason.
Everyone wants to know more, few can really keep up and provide answers. And as this hitherto niche domain is in the mainstream now, the dynamics are changing dramatically. Besides new entries, existing players keep evolving.
I’ve done the hard work of evaluating solutions, so you don’t have to. An overview of the domain and selection methodology, as presented in Big Data Spain 2018
While the Rio 2016 Olympics are winding down and the final medals are being handed out, we thought we would share a bit of work that was done recently by Rik Van Bruggen to explore a really interesting dataset in Neo4j.
Based on an original public dataset by the UK newspaper The Guardian, Rik completed the medallist dataset to contain over 30,000 Olympians between 1896 and 2012. He created a graph model, loaded the data, and wrote a bunch of example queries that yielded some very interesting results. Join us for this 30 minute webinar where we’ll take you through this great Olympian graph and take the data for a spin yourself afterwards.
Congratulations, your data is up and running in a graph database! This is the first step of many to unlocking the potential in your data. It’s easy to get mired in the complexities of graph technology and forget that real users, mere mortals, will need to use this information to inform mission critical tasks. To get the value out of your graph investment, you’ll need to provide an experience that enables users to explore and visualize your graph data in meaningful ways.
In this talk, we’ll take a hands on approach to applying user-centered strategies and leveraging the latest UI tools to rapidly create great experiences with graph data. Topics will include network analysis queries with Cypher and APOC, tailoring experiences to the intended audience and data, determining the the right visualization for the job and cutting through the clutter on choosing the right visualization tools.
This introduction to graph databases is specifically designed for Enterprise Architects who need to map business requirements to architectural components like graph databases. It explains how and why graphs matter for Enterprise Architecture and reviews the architectural differences between relational and graph models.
The Five Graphs of Government: How Federal Agencies can Utilize Graph TechnologyGreta Workman
In this talk from the Neo4j Government Graphday in DC, Philip Rathle discusses how government agencies are leveraging graph technology to power their applications.
Challenges in the Design of a Graph Database Benchmark graphdevroom
Graph databases are one of the leading drivers in the emerging, highly heterogeneous landscape of database management systems for non-relational data management and processing. The recent interest and success of graph databases arises mainly from the growing interest in social media analysis and the exploration and mining of relationships in social media data. However, with a graph-based model as a very flexible underlying data model, a graph database can serve a large variety of scenarios from different domains such as travel planning, supply chain management and package routing.
During the past months, many vendors have designed and implemented solutions to satisfy the need to efficiently store, manage and query graph data. However, the solutions are very diverse in terms of the supported graph data model, supported query languages, and APIs. With a growing number of vendors offering graph processing and graph management functionality, there is also an increased need to compare the solutions on a functional level as well as on a performance level with the help of benchmarks. Graph database benchmarking is a challenging task. Already existing graph database benchmarks are limited in their functionality and portability to different graph-based data models and different application domains. Existing benchmarks and the supported workloads are typically based on a proprietary query language and on a specific graph-based data model derived from the mathematical notion of a graph. The variety and lack of standardization with respect to the logical representation of graph data and the retrieval of graph data make it hard to define a portable graph database benchmark. In this talk, we present a proposal and design guideline for a graph database benchmark. Typically, a database benchmark consists of a synthetically generated data set of varying size and varying characteristics and a workload driver. In order to generate graph data sets, we present parameters from graph theory, which influence the characteristics of the generated graph data set. Following, the workload driver issues a set of queries against a well-defined interface of the graph database and gathers relevant performance numbers. We propose a set of performance measures to determine the response time behavior on different workloads and also initial suggestions for typical workloads in graph data scenarios. Our main objective of this session is to open the discussion on graph database benchmarking. We believe that there is a need for a common understanding of different workloads for graph processing from different domains and the definition of a common subset of core graph functionality in order to provide a general-purpose graph database benchmark. We encourage vendors to participate and to contribute with their domain-dependent knowledge and to define a graph database benchmark proposal.
Bigdata and ai in p2 p industry: Knowledge graph and inferencesfbiganalytics
Title: Knowledge graph and inference: use cases in online financial market
Abstract: While the knowledge graph is an active research field in machine learning community, this powerful tool is still less known to the people in the industry. In this talk, I will first introduce knowledge graph and inference techniques including the recent developments which combine with deep learning. Then I will talk about several use cases in online financial market: fraud/anomaly detection, lost contact discovery, intelligent search, name disambiguation and etc. I will also briefly mention how to build knowledge graph using neo4j from different data sources.
What you need to know to start an AI company?Mo Patel
An overview of why AI and Deep Learning are hot now? Overview f Machine Intelligence startups. What are the key ingredients for AI startup? How can AI startups compete with big tech companies and areas to focus on for differentiation?
In this webinar we discuss the primary use cases for Graph Databases and explore the properties of Neo4j that make those use cases possible.
We cover the high-level steps of modeling, importing, and querying your data using Cypher and give an overview of the transition from RDBMS to Graph.
Relational databases were conceived to digitize paper forms and automate well-structured business processes, and still have their uses. But RDBMS cannot model or store data and its relationships without complexity, which means performance degrades with the increasing number and levels of data relationships and data size. Additionally, new types of data and data relationships require schema redesign that increases time to market.
A graph database like Neo4j naturally stores, manages, analyzes, and uses data within the context of connections meaning Neo4j provides faster query performance and vastly improved flexibility in handling complex hierarchies than SQL. Join this webinar to learn why companies are shifting away from RDBMS towards graphs to unlock the business value in their data relationships
This introduction to graph databases is specifically designed for Enterprise Architects who need to map business requirements to architectural components like graph databases. It explains how and why graphs matter for Enterprise Architecture and reviews the architectural differences between relational and graph models.
The Five Graphs of Government: How Federal Agencies can Utilize Graph TechnologyGreta Workman
In this talk from the Neo4j Government Graphday in DC, Philip Rathle discusses how government agencies are leveraging graph technology to power their applications.
Challenges in the Design of a Graph Database Benchmark graphdevroom
Graph databases are one of the leading drivers in the emerging, highly heterogeneous landscape of database management systems for non-relational data management and processing. The recent interest and success of graph databases arises mainly from the growing interest in social media analysis and the exploration and mining of relationships in social media data. However, with a graph-based model as a very flexible underlying data model, a graph database can serve a large variety of scenarios from different domains such as travel planning, supply chain management and package routing.
During the past months, many vendors have designed and implemented solutions to satisfy the need to efficiently store, manage and query graph data. However, the solutions are very diverse in terms of the supported graph data model, supported query languages, and APIs. With a growing number of vendors offering graph processing and graph management functionality, there is also an increased need to compare the solutions on a functional level as well as on a performance level with the help of benchmarks. Graph database benchmarking is a challenging task. Already existing graph database benchmarks are limited in their functionality and portability to different graph-based data models and different application domains. Existing benchmarks and the supported workloads are typically based on a proprietary query language and on a specific graph-based data model derived from the mathematical notion of a graph. The variety and lack of standardization with respect to the logical representation of graph data and the retrieval of graph data make it hard to define a portable graph database benchmark. In this talk, we present a proposal and design guideline for a graph database benchmark. Typically, a database benchmark consists of a synthetically generated data set of varying size and varying characteristics and a workload driver. In order to generate graph data sets, we present parameters from graph theory, which influence the characteristics of the generated graph data set. Following, the workload driver issues a set of queries against a well-defined interface of the graph database and gathers relevant performance numbers. We propose a set of performance measures to determine the response time behavior on different workloads and also initial suggestions for typical workloads in graph data scenarios. Our main objective of this session is to open the discussion on graph database benchmarking. We believe that there is a need for a common understanding of different workloads for graph processing from different domains and the definition of a common subset of core graph functionality in order to provide a general-purpose graph database benchmark. We encourage vendors to participate and to contribute with their domain-dependent knowledge and to define a graph database benchmark proposal.
Bigdata and ai in p2 p industry: Knowledge graph and inferencesfbiganalytics
Title: Knowledge graph and inference: use cases in online financial market
Abstract: While the knowledge graph is an active research field in machine learning community, this powerful tool is still less known to the people in the industry. In this talk, I will first introduce knowledge graph and inference techniques including the recent developments which combine with deep learning. Then I will talk about several use cases in online financial market: fraud/anomaly detection, lost contact discovery, intelligent search, name disambiguation and etc. I will also briefly mention how to build knowledge graph using neo4j from different data sources.
What you need to know to start an AI company?Mo Patel
An overview of why AI and Deep Learning are hot now? Overview f Machine Intelligence startups. What are the key ingredients for AI startup? How can AI startups compete with big tech companies and areas to focus on for differentiation?
In this webinar we discuss the primary use cases for Graph Databases and explore the properties of Neo4j that make those use cases possible.
We cover the high-level steps of modeling, importing, and querying your data using Cypher and give an overview of the transition from RDBMS to Graph.
Relational databases were conceived to digitize paper forms and automate well-structured business processes, and still have their uses. But RDBMS cannot model or store data and its relationships without complexity, which means performance degrades with the increasing number and levels of data relationships and data size. Additionally, new types of data and data relationships require schema redesign that increases time to market.
A graph database like Neo4j naturally stores, manages, analyzes, and uses data within the context of connections meaning Neo4j provides faster query performance and vastly improved flexibility in handling complex hierarchies than SQL. Join this webinar to learn why companies are shifting away from RDBMS towards graphs to unlock the business value in their data relationships
This introduction to Cypher is designed specifically for the SQL developer. In this webinar we'll explore a data set using Neo4j and Cypher and compare the approach we might take with a relational database and SQL.
Graphs in Action: Slide 3
Under the Hood: What Graphs are and Where They Fit -- Slide 35
Transform Your Data from RDBMS to Graph: A Worked Example -- Jump to slide 82
The first seminar in the mini-seminars periodical sessions I've prepared and lead in my spare time while being employed at Exigen Services. Kudos, guys!
Since these presentations were spare time hobby - I've decided to share them :)
Hopefully someone will find them useful.
The intro is - what designs patters are about, some simple examples and a lots of colorful images.
Not sure if you should order a burrito or a monad for lunch? Get a quick overview of Object Oriented, Functional and Protocol Oriented programming and learn what all that fuss is about.
Object Graph Mapping with Spring Data Neo4j 3 - Nicki Watt & Michael Hunger @...Neo4j
Nicki and Michael have recently been working together on the project to develop/upgrade the Spring Data Neo4j 3 (SDN) library to take advantage of some of the latest Neo4j 2.0 features. This talk takes a look at what can be expected of the new framework, and how it can be used to help model various different use cases with a simple Java domain model backed by a Neo4j database.
Over the past few years, web-applications have started to play an increasingly important role in our lives. We expect them to be always available and the data to be always fresh. This shift into the realm of real-time data processing is now transitioning to physical devices, and Gartner predicts that the Internet of Things will grow to an installed base of 26 billion units by 2020.
Reactive web-applications are an answer to the new requirements of high-availability and resource efficiency brought by this rapid evolution. On the JVM, a set of new languages and tools has emerged that enable the development of entirely asynchronous request and data handling pipelines. At the same time, container-less application frameworks are gaining increasing popularity over traditional deployment mechanisms.
This talk is going to give you an introduction into one of the most trending reactive web-application stack on the JVM, involving the Scala programming language, the concurrency toolkit Akka and the web-application framework Play. It will show you how functional programming techniques enable asynchronous programming, and how those technologies help to build robust and resilient web-applications.
Digital Publishing for Scale: The Economist and GoC4Media
Video and slides synchronized, mp3 and slide download available at URL https://bit.ly/2CALlGE.
Kathryn Jonas talks about The Economist’s struggles and victories in transitioning to Go and how Go has uniquely fit their digital publishing goals. Filmed at qconnewyork.com.
Kathryn Jonas is the Lead Engineer for the Content Platform at The Economist. She has lead projects for organizations in Beijing, London, and New York, applying technology to diverse challenges such as mission impact evaluation, editorial transparency and trust, and online learning and collaboration.
This DrupalCon 2019 Amsterdam talk provides a look beyond the world of PHP and Javascript. It explores how other languages such as Ruby, Java, Rust and Perl handle things and highlights some interesting features of those languages. Not all the things that other languages can do can be done in PHP or Javascript but the concepts and ideas can still be used.
Sparklis exploration et interrogation de points d'accès sparql par interactio...SemWebPro
Sparklis est une application Web de recherche sémantique qui fonctionne au-dessus de points d'accès SPARQL. Il n'est pas lié à un point d'accès particulier, mais peut fonctionner avec n'importe quel point d'accès public ou privé. Le principe de Sparklis est de permettre aux utilisateurs d'explorer et interroger les données en les guidant dans la construction de requêtes puissantes en langue naturelle (anglais ou français). Une requête SPARQL est construite en même temps mais elle est seulement affichée en bas de la page pour l'utilisateur curieux ou pour l'expert qui souhaite la réutiliser dans un autre outil. Les utilisateurs n'ont pas besoin de connaître le schéma de données ou le vocabulaire car ils le découvrent à la volée en naviguant. Ils n'ont rien à écrire, à part les valeurs de filtrage (ex., mots-clés, seuils), ce qui exclut toute erreur lexicale, syntaxique ou sémantique. Sparklis couvre un large sous-ensemble de SPARQL : motifs de graphes, OPTIONAL, UNION, NOT EXISTS, tri des résultats, agrégations, filtres principaux (mots clés, inégalités et intervalles, tag de langue et datatype). Enfin, il est conçu pour passer à l'échelle de gros jeux de données et fonctionne par exemple sur DBpedia (plusieurs milliards de triplets).
Sparklis est en ligne depuis avril 2014 et depuis, des centaines d'utilisateurs l'ont utilisé sur des centaines de points d'accès. Sparklis s'appuie sur les standards du W3C : SPARQL pour l'interrogation, HTML5/CSS3 et Javascript pour l'interface et l'interaction.
Une démonstration montrera aux participants comment Sparklis permet de répondre aux questions du challenge QALD sur DBpedia. Ces questions couvrent différents types de recherche : faits de base (Give me the homepage of Forbes), listes d'entités (Which rivers flow into a German lake?), comptages (How many languages are spoken in Colombia), optimums (Which of Tim Burton's films had the highest budget}). Il est aussi possible de répondre à des questions analytiques plus complexes telles que Give me the total runtime, from highest to lowest, of films per director and per country.
Esta charla comprende las lecciones aprendidas convirtiendo la app de Android de Teambox (una app repleta de deuda técnica y con un alto nivel de acoplamiento entre clases), en la versión actual de Redbooth, que intenta cumplir la arquitectura Hexagonal y los principios SOLID. Durante la exposición explicaremos como fuimos desenredando el código paso a paso; como aplicamos por partes los conceptos de la arquitectura hexagonal; como dejamos de lado componentes del framework de Android que dificultaban el mantenimiento de la app; y que errores cometimos, como los solucionamos y como se podrían haber evitado.
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.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
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.
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
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.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
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.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
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
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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/
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Building better applications for business users with SAP Fiori.
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Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
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.
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Monitoring Java Application Security with JDK Tools and JFR Events
GraphConnect Europe 2016 - Navigating All the Knowledge - James Weaver
1. Navigate *All* the KnowledgeNavigate *All* the Knowledge
Getting started with ConceptMap.ioGetting started with ConceptMap.io
James L. Weaver
Developer Advocate
Twitter: @JavaFXpert
Email: jweaver@pivotal.io
http://JavaFXpert.com
http://CulturedEar.com
http://ConceptMap.io
2. About the PresenterAbout the Presenter
Java Champion, JavaOne Rockstar, plays well with others, etc :-)
Author of several Java/JavaFX/RaspPi books
3. App is live atApp is live at ConceptMap.ioConceptMap.io
ConceptMap.io source code for services and UI:
Open source, licensed under the Apache License, Version 2.0
https://github.com/JavaFXpert/wikibrowser-service
Note: These Technical Presentation slides are available at
as well as by clicking the Help button in
http://slides.com/javafxpert/conceptmap-technical
ConceptMap.io
4. Wikimedia has many projectsWikimedia has many projects
Graphic from presentation by Lynda Pintscher
5. ... the most famous is Wikipedia... the most famous is Wikipedia
Graphic from 2013 presentation by Lynda Pintscher
6. Graphic from 2013 presentation by Lynda Pintscher
Wikimedia CommonsWikimedia Commons
Media files leveraged by Wikimedia projects
7. Graphic from 2013 presentation by Lynda Pintscher
WikidataWikidata
Central storage for the structured data of Wikimedia projects
8. Graphic from 2013 presentation by Lynda Pintscher
WikidataWikidata
Provides semantic structure for Wikipedia articles in any language
29. Use case: Pin Earth to graphUse case: Pin Earth to graph
30. Resource controllerResource controller
http://example/graph?items=Q2,Q405,Q525
Note: Because is on the classpath,
Spring’s is automatically
chosen to convert the GraphResponseNear instance to JSON
Jackson 2
MappingJackson2HttpMessageConverter
@RestController
public class WikiGraphController {
@RequestMapping(value = "/graph", method = RequestMethod.GET,
produces = MediaType.APPLICATION_JSON_VALUE
public ResponseEntity<Object> search(@RequestParam(value = "items", defaultValue="")
String items) {
GraphResponseNear graphResponseNear = null;
...
return Optional.ofNullable(graphResponseNear)
.map(cr -> new ResponseEntity<>((Object)cr, HttpStatus.OK))
.orElse(new ResponseEntity<>("Graph query unsuccessful",
HttpStatus.INTERNAL_SERVER_ERROR));
}
}
To learn more, see Spring GuideBuilding a RESTful Web Service
31. http://example/graph?items=Q2,Q405,Q525
MATCH (a:Item), (b:Item)
WHERE a.itemId IN ['Q2', 'Q405', 'Q525']
AND b.itemId IN ['Q2', 'Q405', 'Q525']
WITH a, b
OPTIONAL MATCH (a)-[rel]-(b)
RETURN a, b, collect(rel)
Neo4j Cypher queryNeo4j Cypher query
(find all relationships between pinned items)
32. Resource representationResource representation
public class Item {
private String type;
private String id;
public Item() {
}
public String getType() {
return type;
}
public void setType(String type) {
this.type = type;
}
public String getId() {
return id;
}
public void setId(String id) {
this.id = id;
}
}
35. Use case: Breadth-first searchUse case: Breadth-first search
(expand items related by a given property to a given depth)
36. Use case: Items in commonUse case: Items in common
Text
(all shortest paths, two hops or less)
37. Neo4j Cypher queryNeo4j Cypher query
http://example/visshortpaths?id=Q111&target=Q313
MATCH p=allShortestPaths(
(a:Item {itemId:'Q111'})-[*..2]-(b:Item {itemId:'Q313'})
)
RETURN p LIMIT 200
(all shortest paths, two hops or less)
38. Use case: Navigate to rootUse case: Navigate to root
(shortest path to Entity using subclass of, instance of, part of)
39. Neo4j Cypher queryNeo4j Cypher query
http://example/visrootpaths?id=Q332
MATCH p=shortestPath(
(a:Item {itemId:'Q332'})-[*]->(b:Item {itemId:'Q35120'})
)
WHERE NONE(x IN RELATIONSHIPS(p)
WHERE (x.propId <> 'P279') AND
(x.propId <> 'P31') AND
(x.propId <> 'P361')
)
RETURN p
(shortest path to Entity using subclass of, instance of, part of)
40. Use case: Degrees of separationUse case: Degrees of separation
Text
(shortest path, like Kevin Bacon game)
41. Make the app executableMake the app executable
package com.javafxpert.wikibrowser;
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.boot.context.properties.EnableConfigurationProperties;
@EnableConfigurationProperties
@SpringBootApplication
public class WikiBrowserServiceApplication {
public static void main(String[] args) {
SpringApplication.run(WikiBrowserServiceApplication.class, args);
}
}
To learn more, see Spring GuideBuilding a RESTful Web Service
42. App build/deploy cycleApp build/deploy cycle
1. $ mvn clean install
2. $ cf push -p ./target/wikibrowser-service.jar ConceptMap
Note: One method of deployment for Spring Boot apps is a JAR
file, which contains an embedded Tomcat servlet container.
45. Navigate *All* the KnowledgeNavigate *All* the Knowledge
ConceptMap.io from a technical perspectiveConceptMap.io from a technical perspective
James L. Weaver
Developer Advocate
Twitter: @JavaFXpert
Email: jweaver@pivotal.io
http://JavaFXpert.com
http://CulturedEar.com
http://ConceptMap.io
Hope you enjoyed