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GraphTour - Popular Use Cases
This document provides an overview of Neo4j, including: - Neo4j is a graph database company with over 260 employees and $80M in funding. - It has over 10M downloads and 275+ enterprise customers, including top retail, financial, and software firms. - Neo4j is used for common use cases like recommendations, fraud detection, knowledge graphs, and master data management by customers like NASA, eBay, Walmart, and Marriott. - The document describes several customer case studies and how Neo4j helped organizations like NASA, ICIJ, and others solve problems and gain insights.
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GraphTour - Popular Use Cases
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- 2. Neo4j - TheGraph Company 7 00+ 7/10 12/25 8/10 53K+ 100+ 300+ 450+ Adoption Top Retail Firms Top Financial Firms Top Software Vendors Customers Partners • Creator of the Neo4j Graph Platform • ~260 employees • HQ in Silicon Valley, other offices include London, Munich, Paris and Malmö (Sweden) • $80M in funding from Fidelity, Sunstone, Conor, Creandum, and Greenbridge Capital • Over 10M+ downloads, • 275+ enterprise subscription customers with over half with >$1B in revenue Ecosystem Startups in program Enterprise customers Partners Meet up members Events per year Industry’s Largest Dedicated Investment in Graphs
- 3. “Neo4j continues to dominatethe graph database market.” 69% of enterprises plan to implement graph databases within the next 12 months. Noel Yuhanna Forrester Market Overview: Graph Database Vendors October 2017 Graph Market Acceleration
- 4. Neo4j — Changingthe World ICIJ used Neo4j to uncover the world’s largest journalistic leak to date, The Panama Papers, exposing criminals, corruption and extensive tax evasion. The US space agency uses Neo4j for their “Lessons Learned” database to connect information to improve search ability effectiveness in space mission. eBay uses Neo4j to enable machine learning through knowledge graphs powering “conversational commerce”. Knowledge Graph for AIFraud Detection Knowledge Graph for humans
- 5. Why Neo4j? The #1Platform for Connected Data
- 6. 6 Real-Time Recommendations Fraud Detection Network & IT Operations MasterData Management Knowledge Graph Identity & Access Management Common Graph Technology Use Cases AirBnb
- 7. Neoj4’s Amazing Customers NASAexplores graph database for deep insights into space International Consortium of Investigative Journalists Wins Pulitzer Prize
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- 12. “Lessons Learned Database” Ahalf-century of collective NASA engineering knowledge
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- 15. Let’s Hear aFew Stories Impact
- 16. Let’s Hear aFew Stories — David Meza, Chief Knowledge Architect at NASA “Neo4j saved well over two years of work and one million dollars of taxpayer funds.” Impact
- 17. Use cases onhttps://neo4j.com/use-cases/
- 18. Business Problem • Optimizewalmart.com user experience • Connect complex buyer and product data to gain super-fast insight into customer needs and product trends • RDBMS couldn’t handle complex queries Solution and Benefits • Replaced complex batch process real-time online recommendations • Built simple, real-time recommendation system with low-latency queries • Serve better and faster recommendations by combining historical and session data Background • Founded in 1962 and based in Arkansas • 11,000+ stores in 27 countries with walmart.com online store • 2M+ employees and $470 billion in annual revenues Walmart RETAIL Real-Time Recommendations18
- 19. Background • One ofthe world’s largest logistics carriers • Projected to outgrow capacity of old system • New parcel routing system Single source of truth for entire network B2C and B2B parcel tracking Real-time routing: up to 7M parcels per day Business Problem • Needed 365x24x7 availability • Peak loads of 3000+ parcels per second • Complex and diverse software stack • Need predictable performance, linear scalability • Daily changes to logistics network: route from any point to any point Solution and Benefits • Ideal domain fit: a logistics network is a graph • Extreme availability, performance via clustering • Greatly simplified routing queries vs. relational • Flexible data model reflect real-world data variance much better than relational • Whiteboard-friendly model easy to understand Accenture LOGISTICS 19 Real-Time Routing Recommendations
- 20. Background • Large globalbank • Deploying Reference Data to users and systems • 12 data domains, 18 datasets, 400+ integrations • Complex data management infrastructure Business Problem • Master data silos were inflexible and hard to consume • Needed simplification to reduce redundancy • Reduce risk when data is in consumers’ hands • Dramatically improve efficiency Solution and Benefits • Data distribution flows improved dramatically • Knowledge Base improves consumer access • Ad-hoc analytics improved • Governance, lineage and trust improved • Better service level from IT to data consumers UBS FINANCIAL SERVICES Master Data Management / Metadata20 CE Customer since 2016 QEE Customer since 2015
- 21. Background • Large NordicTelecom Provider • 1M Broadband routers deployed in Sweden • Half of subscribership are over 55yrs old • Each household connects 10 devices • Goal to improve customer experience Business Problem • Broadband router enhancement to improve customer experience • Context-based in home services • How to build smart home platform that allows vendors to build new “home-centric” apps Solution and Benefits • New Features deployed to 1M homes • API-based platform for easy apps that: • Automatically assemble Spotify playlists based on who is in the house • Notify parents when children get home • Build smart shopping lists TELIA ZONE TELECOMMUNICATIONS Smart Home / Internet of Things21 EE Customer since 2016 Q
- 22. Background • World's largesthospitality / hotel company • 7th largest web site on internet • 1.5 M hotel rooms offered online by 2018 • Revenue Management System that allows property managers to update their pricing rates Business Problem • Provide the right room & price at the right time • Old rate program was inflexible and bogged down as they increased the pricing options per property per day • Lay the path to be an innovator in the future Solution and Benefits • 2016-era rate program embeds Neo4j as "cache" • Created a graph per hotel for 4500 properties in 3 clusters • 1000% increase in volume over 4 years • 50% decrease in infrastructure costs • "Use Neo4j Support!" MARRIOTT TRAVEL & HOSPITALITY SERVICES Pricing Recommendations Engine22 EE Customer since 2014 Q2
- 23. Background • Personal shoppingassistant • Converses with buyer via text, picture and voice to provide real-time recommendations • Combines AI and natural language understanding (NLU) in Neo4j Knowledge Graph • First of many apps in eBay's AI Platform Business Problem • Improve personal context in online shopping • Transform buyer-provided context into ideal purchase recommendations over social platforms • "Feels like talking to a friend" Solution and Benefits • 3 developers, 8M nodes, 20M relationships • Needed high-performance traversals to respond to live customer requests • Easy to train new algorithms and grow model • Generating revenue since launch eBay ShopBot ONLINE RETAIL Knowledge Graph powers Real-Time Recommendations23 EE Customer since 2016 Q3
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- 30. Use case: KnowledgeGraphs
- 31. Use case: FraudAnalytics
- 32. Use case: Identityand Access Management
- 33. Use case: Masterdata management
- 34. Use case: Networkand IT Operations
- 35. Use case: Real-timeRecommendations
- 36. Use case: SocialNetworks
- 37. Use case: Graph-basedAI & Analytics
- 38. Popular Graph TechnologyUse Cases for AI and Analytics
- 39. Customer stories onhttps://neo4j.com/customers/
- 40. Software Financial Services Teleco m Retail & ConsumerGoods Media & Entertainment Other Industries Airbus
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- 53. Development & Administration Analytics Tooling Graph Analytics Graph Transactions Data Integration Discovery& VisualizationDrivers & APIs A I Neo4j Database • 50% faster writes • Real-time transactions and traversal applications The Neo4j Graph Platform surrounds Neo4j Neo4j Desktop, the developers’ mission control console • Free, registered local license of Enterprise Edition • APOC library installer • Algorithm library installer Data Integration • Neo4j ETL reveals RDBMS hidden relationships upon importing to graph • Data Importer for fast data ingestion • Data Lake integrator materializes graphs from Apache Hadoop, Hive and Spark Graph Analytics • Graph Algorithms support PageRank, Centrality and Path Finding • Cypher for Apache Spark from openCypher.org supports graph composition (sub-graphs) and algorithm chaining Discovery & Visualization • Integration with popular visualization vendors • Neo4j Browser and custom visualizations allow graph exploration Bolt, GraphQL, Java and more • Secure, Causal Clustering • High-speed analytic processing • On-prem, Docker & cloud delivery
- 54. Native Graph Database Technology Internet-scale,native graph database which executes connected workloads faster than any other database management system. Neo4j – Fastest Path to Graph Success Highest Investment in Customer Success Largest ecosystem of solutions and graph based services to reduce learning curve and time to market Innovation Network Highest concentration of Graph Innovators, Experts, Analysts and Developers.
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