Vena is a service delivery platform that uses a graph database to distribute linear broadcast video around the UK. The graph model represents physical network resources, logical resources, services, and customers with relationships. This enables feasibility checking, resource reservation, service fulfillment, and service impact analysis when failures occur. The system aims to provide low latency, low jitter, high bandwidth distribution with automated service lifecycle management and customer self-service capabilities.
Sopra Steria: Intelligent Network Analysis in a Telecommunications EnvironmentNeo4j
The Intelligent Network Analyzer (INA) uses the graph database by Neo4j to build a digital twin of the mobile telecommunications network. Based on this digital twin, INA can be used to efficiently perform various analyses to support network operators in their daily business. In our talk, we will show some features of INA and explain how they draw on the particular strengths of the Neo4j graph database.
SITA WorldTracer - the global Lost and Found solution built on Neo4j cuts costs and speeds delivery at airports worldwide by returning lost property to travelers.
The three layers of a knowledge graph and what it means for authoring, storag...Neo4j
In this talk, Katariina Kari will discuss a framework for building a Knowledge Graph, by distinguishing between concepts, categories, and data. All three are interconnected to each other, however, they differ in their order of magnitude and the way they come about. A distinction makes sense to understand who is responsible for which part of the knowledge graph. Also, each layer should be governed differently. This framework ultimately helps to create a division of labour inside the company and helps stakeholders to understand the knowledge graph better.
Modern Data Challenges require Modern Graph TechnologyNeo4j
This session focuses on key data trends and challenges impacting enterprises. And, how graph technology is evolving to future-proof data strategy and architectures.
Sopra Steria: Intelligent Network Analysis in a Telecommunications EnvironmentNeo4j
The Intelligent Network Analyzer (INA) uses the graph database by Neo4j to build a digital twin of the mobile telecommunications network. Based on this digital twin, INA can be used to efficiently perform various analyses to support network operators in their daily business. In our talk, we will show some features of INA and explain how they draw on the particular strengths of the Neo4j graph database.
SITA WorldTracer - the global Lost and Found solution built on Neo4j cuts costs and speeds delivery at airports worldwide by returning lost property to travelers.
The three layers of a knowledge graph and what it means for authoring, storag...Neo4j
In this talk, Katariina Kari will discuss a framework for building a Knowledge Graph, by distinguishing between concepts, categories, and data. All three are interconnected to each other, however, they differ in their order of magnitude and the way they come about. A distinction makes sense to understand who is responsible for which part of the knowledge graph. Also, each layer should be governed differently. This framework ultimately helps to create a division of labour inside the company and helps stakeholders to understand the knowledge graph better.
Modern Data Challenges require Modern Graph TechnologyNeo4j
This session focuses on key data trends and challenges impacting enterprises. And, how graph technology is evolving to future-proof data strategy and architectures.
Andrea Bielli, IT Architect Global Digital Solution, Enel
Davide Gimondo, Software Engineer, Enel
Enel mostra come neo4j aiuta nella gestione delle reti elettriche in 8 paesi nel mondo.
Con l’obiettivo di ottimizzare gli algoritmi di percorrenza della rete elettrica, in modo da rendere le reti sempre più efficienti e resilienti.
L’obiettivo di Enel è una gestione ottimale della topologia della rete per garantire gli obiettivi del gruppo: la transizione energetica e l’elettrificazione dei paesi in cui opera, verso l’obiettivo Net Zero, relativo alla riduzione delle emissioni nella produzione e distribuzione dell’energia elettrica.
Transforming BT’s Infrastructure Management with Graph TechnologyNeo4j
Join us for this 45-minute discussion on network digital twins and how BT is transforming its infrastructure management with graph technology and Neo4j.
Danish Business Authority: Explainability and causality in relation to ML OpsNeo4j
by Joakim Sandroos, Senior Data Scientist at Danish Business Authority
At the Danish Business Authority (DBA), machine learning (ML) is utilized in the role of decision support. In order to build ethical ML on a solid scientific understanding, explainability and traceability are mission critical. DBA utilizes an in-house developed Directed Acyclic Graph (DAG) tool, RecordKeeper, to preserve causality information between business events on their platform. Via flow analysis, they identify Springs and Sinks in their dataset to mitigate overall model bias.
Banking Circle: Money Laundering Beware: A Modern Approach to AML with Machin...Neo4j
by Ruben Menke, Lead Data Scientist at Banking Circle
In this talk, Banking Circle will show how a modern computational method is essential in the fight against money laundering.
Sopra Steria: Intelligent Network Analysis in a Telecommunications EnvironmentNeo4j
The Intelligent Network Analyzer (INA) uses the graph database by Neo4j to build a digital twin of the mobile telecommunications network. Based on this digital twin, INA can be used to efficiently perform various analyses to support network operators in their daily business. In our talk, we will show some features of INA and explain how they draw on the particular strengths of the Neo4j graph database.
Smarter Fraud Detection With Graph Data ScienceNeo4j
Join us for this 20-minute webinar to hear from Nick Johnson, Product Marketing Manager for Graph Data Science, to learn the basics of Neo4j Graph Data Science and how it can help you to identify fraudulent activities faster.
SERVIER Pegasus - Graphe de connaissances pour les phases primaires de recher...Neo4j
Jérémy Grignard, Data & Research Scientist, Servier
Les données que nous exploitons sont issues de domaines scientifiques variés comme les sciences omiques, structurales, cellulaires, chimiques ou phénotypiques, et correspondent à des concepts pharmaco-biologiques hétérogènes. Nous développons le graphe de connaissances Pegasus qui vise, en plus de capitaliser sur des données actuellement disponibles, à explorer l’environnement complexe des cibles thérapeutiques, à identifier des modalités de criblage pertinentes et à concevoir de nouvelles expériences.
Jesús Barrasa, Head of Solutions Architecture for EMEA, Neo4j
Les graphes de connaissances et le Machine Learning sont les deux principales méthodes de représentation et d’exploitation des connaissances. Ce qui est intéressant et plutôt méconnu, c’est qu’ils sont hautement complémentaires. Cette présentation vous éclairera sur la manière dont ces deux domaines interagissent, mettant en avant la synergie entre eux et comment les variantes les plus récentes du ML (IA générative et LLMs) s’intègrent avec des graphes de connaissances pour construire des applications sémantiques modernes.
Volvo Cars - Retrieving Safety Insights using Graphs (GraphSummit Stockholm 2...Neo4j
Volvo Cars has developed a map attributes representation as a graph in Neo4j. By including real time car data, they are able to collect insights to learn on possible accident causes based on road infrastructure.
The path to success with graph database and graph data science_ Neo4j GraphSu...Neo4j
What’s new, and what’s next? Product innovation moves rapidly at Neo4j – learn how graph technology can provide you with the tools to get much more from your data!
Easily Identify Sources of Supply Chain GridlockNeo4j
Join us for this 20-minute webinar to hear from Nick Johnson, Product Marketing Manager for Graph Data Science, as he explains the fundamentals of Neo4j Graph Data Science and its applications in optimizing supply chain management. Discover how leveraging graph analytics can help you identify bottlenecks, reduce costs, and streamline your supply chain operations more efficiently.
Neo4j GraphSummit London March 2023 Emil Eifrem Keynote.pptxNeo4j
Neo4j Founder and CEO Emil Eifrem shares his story on the origins of Neo4j and how graph technology has the potential to answer the world's most important data questions.
Building a modern data stack to maintain an efficient and safe electrical gridNeo4j
An overview of how our organization transitioned to being data-centric, through the implementation of a Enterprise data backbone, and dedicated tools using Neo4j technology, as the various challenges we faced during the process to make the dream come true.
The Show Must Go On! Using Kafka to Assure TV Signals Reach the TransmittersHostedbyConfluent
"Have you ever wondered how broadcast TV signals get from the sports venues to over a hundred TV transmitters scattered around the United Kingdom? Over 95% of all video signals destined for UK broadcast traverse dedicated networks managed by British Telecom (BT) Networks.
BT’s next generation network infrastructure is a system called Vena. To build Vena, BT embraced Software Defined Wide Area Networks (SD-WAN) as a paradigm to allow users to manage their own services and to quickly establish new video feeds within a few mouse clicks. BT automated the task of alarm monitoring and fault reporting within their network’s operational International Media Centre.
To make Vena tick, BT needs to monitor thousands of complex devices, which could be deployed at race courses, rugby grounds and football stadiums across the country. As well as telemetry data from TV transmitter sites which could be situated on far flung Scottish islands. To handle this, BT turned to Confluent Platform as the backbone of its event handling and alarm correlation infrastructure.
In this talk we will explain the scale of the challenge we faced, how we leveraged Confluent Platform to address it as well as giving a live demonstration of booking a video feed from Birmingham to the Kafka Summit."
Andrea Bielli, IT Architect Global Digital Solution, Enel
Davide Gimondo, Software Engineer, Enel
Enel mostra come neo4j aiuta nella gestione delle reti elettriche in 8 paesi nel mondo.
Con l’obiettivo di ottimizzare gli algoritmi di percorrenza della rete elettrica, in modo da rendere le reti sempre più efficienti e resilienti.
L’obiettivo di Enel è una gestione ottimale della topologia della rete per garantire gli obiettivi del gruppo: la transizione energetica e l’elettrificazione dei paesi in cui opera, verso l’obiettivo Net Zero, relativo alla riduzione delle emissioni nella produzione e distribuzione dell’energia elettrica.
Transforming BT’s Infrastructure Management with Graph TechnologyNeo4j
Join us for this 45-minute discussion on network digital twins and how BT is transforming its infrastructure management with graph technology and Neo4j.
Danish Business Authority: Explainability and causality in relation to ML OpsNeo4j
by Joakim Sandroos, Senior Data Scientist at Danish Business Authority
At the Danish Business Authority (DBA), machine learning (ML) is utilized in the role of decision support. In order to build ethical ML on a solid scientific understanding, explainability and traceability are mission critical. DBA utilizes an in-house developed Directed Acyclic Graph (DAG) tool, RecordKeeper, to preserve causality information between business events on their platform. Via flow analysis, they identify Springs and Sinks in their dataset to mitigate overall model bias.
Banking Circle: Money Laundering Beware: A Modern Approach to AML with Machin...Neo4j
by Ruben Menke, Lead Data Scientist at Banking Circle
In this talk, Banking Circle will show how a modern computational method is essential in the fight against money laundering.
Sopra Steria: Intelligent Network Analysis in a Telecommunications EnvironmentNeo4j
The Intelligent Network Analyzer (INA) uses the graph database by Neo4j to build a digital twin of the mobile telecommunications network. Based on this digital twin, INA can be used to efficiently perform various analyses to support network operators in their daily business. In our talk, we will show some features of INA and explain how they draw on the particular strengths of the Neo4j graph database.
Smarter Fraud Detection With Graph Data ScienceNeo4j
Join us for this 20-minute webinar to hear from Nick Johnson, Product Marketing Manager for Graph Data Science, to learn the basics of Neo4j Graph Data Science and how it can help you to identify fraudulent activities faster.
SERVIER Pegasus - Graphe de connaissances pour les phases primaires de recher...Neo4j
Jérémy Grignard, Data & Research Scientist, Servier
Les données que nous exploitons sont issues de domaines scientifiques variés comme les sciences omiques, structurales, cellulaires, chimiques ou phénotypiques, et correspondent à des concepts pharmaco-biologiques hétérogènes. Nous développons le graphe de connaissances Pegasus qui vise, en plus de capitaliser sur des données actuellement disponibles, à explorer l’environnement complexe des cibles thérapeutiques, à identifier des modalités de criblage pertinentes et à concevoir de nouvelles expériences.
Jesús Barrasa, Head of Solutions Architecture for EMEA, Neo4j
Les graphes de connaissances et le Machine Learning sont les deux principales méthodes de représentation et d’exploitation des connaissances. Ce qui est intéressant et plutôt méconnu, c’est qu’ils sont hautement complémentaires. Cette présentation vous éclairera sur la manière dont ces deux domaines interagissent, mettant en avant la synergie entre eux et comment les variantes les plus récentes du ML (IA générative et LLMs) s’intègrent avec des graphes de connaissances pour construire des applications sémantiques modernes.
Volvo Cars - Retrieving Safety Insights using Graphs (GraphSummit Stockholm 2...Neo4j
Volvo Cars has developed a map attributes representation as a graph in Neo4j. By including real time car data, they are able to collect insights to learn on possible accident causes based on road infrastructure.
The path to success with graph database and graph data science_ Neo4j GraphSu...Neo4j
What’s new, and what’s next? Product innovation moves rapidly at Neo4j – learn how graph technology can provide you with the tools to get much more from your data!
Easily Identify Sources of Supply Chain GridlockNeo4j
Join us for this 20-minute webinar to hear from Nick Johnson, Product Marketing Manager for Graph Data Science, as he explains the fundamentals of Neo4j Graph Data Science and its applications in optimizing supply chain management. Discover how leveraging graph analytics can help you identify bottlenecks, reduce costs, and streamline your supply chain operations more efficiently.
Neo4j GraphSummit London March 2023 Emil Eifrem Keynote.pptxNeo4j
Neo4j Founder and CEO Emil Eifrem shares his story on the origins of Neo4j and how graph technology has the potential to answer the world's most important data questions.
Building a modern data stack to maintain an efficient and safe electrical gridNeo4j
An overview of how our organization transitioned to being data-centric, through the implementation of a Enterprise data backbone, and dedicated tools using Neo4j technology, as the various challenges we faced during the process to make the dream come true.
The Show Must Go On! Using Kafka to Assure TV Signals Reach the TransmittersHostedbyConfluent
"Have you ever wondered how broadcast TV signals get from the sports venues to over a hundred TV transmitters scattered around the United Kingdom? Over 95% of all video signals destined for UK broadcast traverse dedicated networks managed by British Telecom (BT) Networks.
BT’s next generation network infrastructure is a system called Vena. To build Vena, BT embraced Software Defined Wide Area Networks (SD-WAN) as a paradigm to allow users to manage their own services and to quickly establish new video feeds within a few mouse clicks. BT automated the task of alarm monitoring and fault reporting within their network’s operational International Media Centre.
To make Vena tick, BT needs to monitor thousands of complex devices, which could be deployed at race courses, rugby grounds and football stadiums across the country. As well as telemetry data from TV transmitter sites which could be situated on far flung Scottish islands. To handle this, BT turned to Confluent Platform as the backbone of its event handling and alarm correlation infrastructure.
In this talk we will explain the scale of the challenge we faced, how we leveraged Confluent Platform to address it as well as giving a live demonstration of booking a video feed from Birmingham to the Kafka Summit."
High Scalability Network Performance Management for EnterprisesCA Technologies
CA Performance Management is a big data collection, warehousing and analytics solution that helps enterprises maximize return on their network infrastructure investments and lower the cost of network operations.
Learn more about CA Performance Management here: http://bit.ly/1vrQPJB
DEVNET-1153 Enterprise Application to Infrastructure Integration – SDN AppsCisco DevNet
We've all heard about SDN and how SDN provides flexible networks to solve networks operation challenges. With respect to SDN Applications, the most obvious conversation is about network applications and services. But today we will discuss how we at Cisco are addressing business challenges and impact business outcomes directly by connecting two disparate worlds of Enterprise applications (EA) and Networking stack using Cisco Integration Platform (CIP).
High Scalability Network Monitoring for Communications Service ProvidersCA Technologies
CA Performance Management is a big data collection, warehousing and analytics solution that helps communications service providers maximize return on their network infrastructure investments and lower the cost of network operations.
Learn more about CA Performance Management here: http://bit.ly/1vrQPJB
RAN dimensioning: Lessons learned by TelstraWi-Fi 360
When investing CAPEX in capacity related Radio Access Network infrastructure, Telstra tries to balance a number of competing goals: maximize the customer experience; for the largest number of customers; with the most effective use of invested capital; through the selective expansion of network hardware.
Because modern wireless networks rely on soft capacity to efficiently provide as much capacity as possible, proper RAN dimensioning must be able to accurately take the effects of soft capacity into account. Current methodology for KPI thresholds, however, cannot provide an accurate understanding of customer experience.
During this exclusive webinar featuring prominent speakers from Telstra, Ascom and Maravedis-Rethink, we will discuss a more effective approach to understanding the relationship of soft capacity and customer experience.
Participants in the webinar will learn how this better approach to RAN dimensioning can lead to improved customer experience and more efficient use of CAPEX.
In addition, Research Director Caroline Gabriel will discuss the broader issues of optimizing and dimensioning the access network, with relation to recent research conducted with a broad base of major mobile operators worldwide.
The CoreSite Interconnect Gateway™ (CIG) solution was created with optimal performance and cost efficiency in mind. CIG allows you to hit the “easy button” to rapidly enhance your network performance. This fully managed solution creates secure, high-bandwidth direct connectivity to leading public clouds, network service providers, data centers, and corporate offices to improve application performance and reduce network costs. Traffic is efficiently routed between vendors through router, firewall and WAN acceleration services on the platform.
CISCO: Accelerating Small Cell Deployments in the EnterpriseSmall Cell Forum
Mark Grayson, distinguished engineer at CISCO presented on the Small Cell Forum stand at MWC on accelerating small cell deployments within the enterprise zone.
On-Demand Production Infrastructure delivered Just In Time By Shane Guthrie o...ETCenter
Today's productions increasingly demand the rapid provisioning and integration of core resources in order to support increasingly complex workflows across multiple partners. The integration of Workflow software to Infrastructure as a Service (IaaS) pools for compute, storage, and network is finally within reach with the advent of provisioning technologies like Software Defined Networking, API Abstraction, Orchestration and Transformation, and Network Function Virtualization (NFV). This track will discuss the evolution of the IaaS marketplace and the new business models that are cropping up as a result.
Similar to BT Group: Use of Graph in VENA (a smart broadcast network) (20)
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.
Workshop 1. Architecting Innovative Graph Applications
Join this hands-on workshop for beginners led by Neo4j experts guiding you to systematically uncover contextual intelligence. Using a real-life dataset we will build step-by-step a graph solution; from building the graph data model to running queries and data visualization. The approach will be applicable across multiple use cases and industries.
LARUS - Galileo.XAI e Gen-AI: la nuova prospettiva di LARUS per il futuro del...Neo4j
Roberto Sannino, Larus Business Automation
Nel panorama sempre più complesso dei progetti basati su grafi, LARUS ha consolidato una solida esperienza pluriennale, costruendo un rapporto di fiducia e collaborazione con Neo4j. Attraverso il LARUS Labs, ha sviluppato componenti e connettori che arricchiscono l’ecosistema Neo4j, contribuendo alla sua continua evoluzione. Tutto questo know-how è stato incanalato nell’innovativa soluzione Galileo.XAI di LARUS, un prodotto all’avanguardia che, integrato con la Generative AI, offre una nuova prospettiva nel mondo dell’Intelligenza Artificiale Spiegabile applicata ai grafi. In questo speech, si esplorerà il percorso di crescita di LARUS in questo settore, mettendo in luce le potenzialità della soluzione Galileo.XAI nel guidare l’innovazione e la trasformazione digitale.
GraphSummit Milan - Visione e roadmap del prodotto Neo4jNeo4j
van Zoratti, VP of Product Management, Neo4j
Scoprite le ultime innovazioni di Neo4j che consentono un’intelligenza guidata dalle relazioni su scala. Scoprite le più recenti integrazioni nel cloud e i miglioramenti del prodotto che rendono Neo4j una scelta essenziale per gli sviluppatori che realizzano applicazioni con dati interconnessi e IA generativa.
GraphSummit Milan & Stockholm - Neo4j: The Art of the Possible with GraphNeo4j
Dr Jesús Barrasa, Head of Solutions Architecture for EMEA, 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.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
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Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
3. What is Vena?
If you are watching ITV or C4 and soon any terrestrial TV
channel you are seeing Vena at work
• Vena is a service delivery platform for linear broadcast quality video distribution
around the UK
• Vena is a fully automated platform both in terms of commissioning equipment and in
allowing customers to order services
• Vena was created to provide best in class performance for media traffic, with;
▪ low latency
▪ low jitter
▪ high bandwidth
▪ Multicast point to multi-point
• Customer self serve for managing and tracking services
4. Opportunity – Renewal of obsolescent
infrastructure and management systems
BT Group | Public 4
Leverage this transformation to fulfil BT M&B key business objectives in terms of competitiveness, operational effectiveness and
data integrity
Area Opportunity IT System requirements KPIs
Increased competitiveness and Customer
Experience
• Decreased time to market by automated
service life cycle management
• Deploy a platform capable of supporting
the creation of innovative and competitive
service bundles for broadcaster
• Provide customers with simplified self
serve service ordering
• Modular functional architecture for
vertical and horizontal scaling.
• Adoption Microservices
• Model/Intent-driven network services.
• Service delivery times
• Market Share & Revenue
• Number of new services launched
• Number of new service bundles launched
Operational Effectiveness and Data Integrity • Decrease operational cost by minimizing
human intervention from service
fulfilment to assurance
• Data model structure to ensure real time
resource status
• Guarantee end to end view of services
• Closed loop automation
• E2E topology view
• Central Dynamic inventory
• Service, resources, live data correlation
for service management decisions
• Number of repair calls completed
• Cost reduction related to inventory
changes.
5. Architectural Principles
BT Group | Public 5
Layering Service view vs network view with
relationships between them
Service Fulfilment Service fulfilment needs real real-
time path computation which
needs to honour BT and customer
constraints
Operational response
Improvements
Avoid alarm fatigue for operations
- Provide an enriched and
correlated alarm to operations
rather than bombarding hundreds
of isolated and unrelated alarm
Resilience and reliability 99.999 %
Service Fulfilment Service fulfilment needs real real-
time path computation which
needs to honour BT and customer
constraints
Development flexibility Minimize lead time to build new
service types
Architectural complexity Minimize system integration costs
Top functional requirements Non-functional requirements
6. Layered model for Resource & Services
BT Group | Public 6
We wanted to create a layered inventory where we have
physical resources, logical resources, services and customers
with relationships, which enables
• Feasibility check of a service
• Reservation of resources
• Service Fulfilment
• Service Impact Analysis
7. Path Computation
BT Group | Public 7
Set up a path computation service to calculate a path from a
source to multiple destinations considering the following
constraints –
• Node and Link Diversity - The primary and protected paths cannot
use the same links and nodes
• Cost of the Link – which is a function of latency and bandwidth
• Bandwidth Optimization - for a tree, we split as late as possible so as
to optimize node and link bandwidth usage
• MPLS constraint – we don’t loop back to a node we visited when
calculating a path
The time between call and response needs to be in
milliseconds.
8. Service Impacts
BT Group | Public 8
The requirement here, was to create a "Service Impact
Analysis" service. The primary role of this service is to identify
which services are impacted for which customers and the type
of impact.
We want to expose this as a callable API. We want to then call
this API using the identifier of the node/link that failed.
This internally queries the database and calculates
• Services impacted
• The type of impact – e.g. is this a loss of resilience/loss of service
• Customers impacted
We can consolidate this information and instead of flooding ops
with hundreds of alarms, only send enriched and correlated
alarms.
9. Vena
~580 routers
• Juniper (core)
• Cisco (CPE)
• AppearTV (CPE)
~1000 links
▪ Mostly Openreach circuits
▪ Some in-building
connections
▪ A handful of microwave
connections
BT Group PowerPoint | 9
~770 live services
~2,300 total services
~10 events/second
▪ SNMP traps
▪ Syslog messages
~52,000 nodes
~384,000 relationships
Today:
▪ ITV
▪ UK Rugby
▪ Some Racing TV
Soon:
▪ Arqiva
▪ BBC
▪ More Racing TV
▪ … and more
BT’s network for broadcast media
10. Lessons Learnt
Beware clustering
▪ Neo4j is ACID compliant
▪ But also, eventually
consistent
BT Group | Public 10
SDN5 to SDN6 migration
▪ Think JPA
▪ Not lazily loaded, risk of
loading the entire graph
memory.
Performance
▪ Worth considering using
graph experts to review
queries and models