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.
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.
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.
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.
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.
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.
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 ScienceNeo4j
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!
Optimizing Your Supply Chain with the Neo4j GraphNeo4j
With the world’s supply chain system in crisis, it’s clear that better solutions are needed. Digital twins built on knowledge graph technology allow you to achieve an end-to-end view of the process, supporting real-time monitoring of critical assets.
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.
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.
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.
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.
Graph Machine Learning in Production with Neo4jNeo4j
In our presentation at Data Innovation Summit 2023, we explained how you could accelerate AI and machine learning innovation by using graph data science.
This comes down to three things: 1. Getting your data into a graph
2. Use graph algorithms to find what’s important
3. Use machine learning to make predictions on your graph
We covered these three key steps with code examples and discussed some key considerations when moving your ML workloads to production.
At Neo4j we believe that ‘Graphs Are Everywhere’. In this session, we’ll be looking specifically at graphs within the Financial Services industry. We’ll review the types of data that are typically available within a bank, illustrate the graphs can be formed from that data, and discuss the use cases that those graphs can enable and support.
The use cases presented will include Anti-Money Laundering and Fraud Detection and Prevention (including integration with AI and Machine Learning technologies), Regulatory Compliance (such as BCBS 239 and GDPR), Customer 360 View, Master Data Management, and Identity and Access Management.
Many players in the Financial Services industry already rely on Neo4j's graph database: such as Lending Club, the world's largest microservices credit marketplace, for Network and IT, the big German insurance company die Bayerische for graph-based search, Cerved for Master Data Management, Wobi for price comparison and real-time recommendation, or UBS for Identity and Access Management.
Neo4j GraphSummit Copenhagen - The Art Of The Possible With Graph Technology ...Neo4j
by Emil Eifrem, CEO at Neo4j
Gartner predicts that “By 2025, graph technologies will be used in 80% of data and analytics innovations, up from 10% in 2021, facilitating rapid decision making across the enterprise.”* This session will explain why.
Neo4j Keynote: The Art of the Possible with Graph TechnologyNeo4j
Hear how companies are using graph technology to leverage the relationships in their connected data to reveal new ways of solving their most pressing business problems and creating new business value for their enterprises. You’ll see real-world use cases that include fraud detection, AI/ML, supply chain management, real-time recommendations, Customer 360, network, and IT operations, and more.
The path to success with Graph Database and Graph Data ScienceNeo4j
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!
Optimizing Your Supply Chain with the Neo4j GraphNeo4j
With the world’s supply chain system in crisis, it’s clear that better solutions are needed. Digital twins built on knowledge graph technology allow you to achieve an end-to-end view of the process, supporting real-time monitoring of critical assets.
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.
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.
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.
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.
Graph Machine Learning in Production with Neo4jNeo4j
In our presentation at Data Innovation Summit 2023, we explained how you could accelerate AI and machine learning innovation by using graph data science.
This comes down to three things: 1. Getting your data into a graph
2. Use graph algorithms to find what’s important
3. Use machine learning to make predictions on your graph
We covered these three key steps with code examples and discussed some key considerations when moving your ML workloads to production.
At Neo4j we believe that ‘Graphs Are Everywhere’. In this session, we’ll be looking specifically at graphs within the Financial Services industry. We’ll review the types of data that are typically available within a bank, illustrate the graphs can be formed from that data, and discuss the use cases that those graphs can enable and support.
The use cases presented will include Anti-Money Laundering and Fraud Detection and Prevention (including integration with AI and Machine Learning technologies), Regulatory Compliance (such as BCBS 239 and GDPR), Customer 360 View, Master Data Management, and Identity and Access Management.
Many players in the Financial Services industry already rely on Neo4j's graph database: such as Lending Club, the world's largest microservices credit marketplace, for Network and IT, the big German insurance company die Bayerische for graph-based search, Cerved for Master Data Management, Wobi for price comparison and real-time recommendation, or UBS for Identity and Access Management.
Neo4j GraphSummit Copenhagen - The Art Of The Possible With Graph Technology ...Neo4j
by Emil Eifrem, CEO at Neo4j
Gartner predicts that “By 2025, graph technologies will be used in 80% of data and analytics innovations, up from 10% in 2021, facilitating rapid decision making across the enterprise.”* This session will explain why.
Neo4j Keynote: The Art of the Possible with Graph TechnologyNeo4j
Hear how companies are using graph technology to leverage the relationships in their connected data to reveal new ways of solving their most pressing business problems and creating new business value for their enterprises. You’ll see real-world use cases that include fraud detection, AI/ML, supply chain management, real-time recommendations, Customer 360, network, and IT operations, and more.
Keynote: Art of the Possible - Chandra RanganNeo4j
Are you drowning in data but lacking in insight? 80% of business leaders say data is critical in decision-making, yet 41% cite a lack of understanding of data because it is too complex or not accessible enough. You’ll learn how companies are using graph technology to leverage the relationships in their connected data to reveal new ways of solving their most pressing business problems and creating new business value for their enterprises. You’ll see real-world use cases that include fraud detection, AI/ML, supply chain management, real-time recommendations, Customer 360, network/IT operations and more.
Are you drowning in data but lacking in insight? 80% of business leaders say data is critical in decision-making, yet 41% cite a lack of understanding of data because it is too complex or not accessible enough. You’ll learn how companies are using graph technology to leverage the relationships in their connected data to reveal new ways of solving their most pressing business problems and creating new business value for their enterprises. You’ll see real-world use cases that include fraud detection, AI/ML, supply chain management, real-time recommendations, Customer 360, network/IT operations and more.
Neo4j : L’art des Possibles avec la Technologie des GraphesNeo4j
Philip Rathle, CTO, Neo4j
Gartner prévoit que “d’ici 2025, les technologies de graphes seront utilisées dans 80 % des innovations en matière de données et d’analyse, contre 10 % en 2021, ce qui facilitera la prise de décision rapide dans toute l’entreprise “*. Cette session explique pourquoi.
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.
Government GraphSummit: Keynote - Graphs in GovernmentNeo4j
Jim Webber Ph.D., Chief Scientist, Neo4j
Learn about the importance of graph technology, its evolution over the last few years and the impact it has had on the database and data analytics industry. This session will provide an overview of graph technology and talk about the past, present, and future of graphs and data management. Multiple use cases and customer examples will be covered, including examples of where graph databases and graph data science can assist and accelerate machine learning and artificial intelligence projects.
Neo4j Jesus Barrasa The Art of the Possible with GraphNeo4j
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.
The Data Platform for Today's Intelligent Applications.pdfNeo4j
Do you know how graph technology is used in today’s data-driven applications? We’ll get you up to speed and introduce you to the Neo4j product portfolio.
Are You Underestimating the Value Within Your Data? A conversation about grap...Neo4j
Are You Underestimating the Value Within Your Data?
A conversation about graph technology
Dr Jesús Barrasa
Head of Field Engineering, Neo4j
Dr Jim Webber
Chief Scientist, Neo4j
Gartner IT Symposium Xpo Barcelona 2022 - Neo4j
Data Mesh is a new socio-technical approach to data architecture, first described by Zhamak Dehghani and popularised through a guest blog post on Martin Fowler's site.
Since then, community interest has grown, due to Data Mesh's ability to explain and address the frustrations that many organisations are experiencing as they try to get value from their data. The 2022 publication of Zhamak's book on Data Mesh further provoked conversation, as have the growing number of experience reports from companies that have put Data Mesh into practice.
So what's all the fuss about?
On one hand, Data Mesh is a new approach in the field of big data. On the other hand, Data Mesh is application of the lessons we have learned from domain-driven design and microservices to a data context.
In this talk, Chris and Pablo will explain how Data Mesh relates to current thinking in software architecture and the historical development of data architecture philosophies. They will outline what benefits Data Mesh brings, what trade-offs it comes with and when organisations should and should not consider adopting it.
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.
Knowledge Graphs and Generative AI
Dr. Katie Roberts, Data Science Solutions Architect, Neo4j
It’s no secret that Large Language Models (LLMs) are popular right now, especially in the age of Generative AI. LLMs are powerful models that enable access to data and insights for any user, regardless of their technical background, however, they are not without challenges. Hallucinations, generic responses, bias, and a lack of traceability can give organizations pause when thinking about how to take advantage of this technology. Graphs are well suited to ground LLMs as they allow you to take advantage of relationships within your data that are often overlooked with traditional data storage and data science approaches. Combining Knowledge Graphs and LLMs enables contextual and semantic information retrieval from both structured and unstructured data sources. In this session, you’ll learn how graphs and graph data science can be incorporated into your analytics practice, and how a connected data platform can improve explainability, accuracy, and specificity of applications backed by foundation models.
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 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.
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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.
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.
LARUS - Galileo.XAI e Gen-AI: la nuova prospettiva di LARUS per il futuro del...Neo4j
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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
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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.
LARUS - Galileo.XAI e Gen-AI: la nuova prospettiva di LARUS per il futuro del...Neo4j
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UNI DI NAPOLI FEDERICO II - Il ruolo dei grafi nell'AI Conversazionale IbridaNeo4j
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CERVED e Neo4j su una nuvola, migrazione ed evoluzione di un grafo mission cr...Neo4j
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Luca Cannistrà, Data Architect Specialist
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LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
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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.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
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!