Neo4j GraphTour Europe 2019

1. Use cases

2. Neo4j - The Graph 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
dominate the 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 — Changing the 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 #1 Platform for Connected Data

6. 6
Real-Time
Recommendations
Fraud
Detection
Network &
IT Operations
Master Data
Management
Knowledge
Graph
Identity & Access
Management
Common Graph Technology Use Cases
AirBnb

7. Neoj4’s Amazing Customers
NASA explores graph database
for deep insights into space
International Consortium of Investigative
Journalists
Wins Pulitzer Prize

8. Johnson Space Center
Houston, Texas

12. “Lessons Learned Database”
A half-century of collective NASA engineering knowledge

13. “Lessons Learned”
Database
GRAPH DB
Load Data

14. “Lessons Learned”
Database
GRAPH DB
Load Data

15. Let’s Hear a Few Stories
Impact

16. Let’s Hear a Few 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 on https://neo4j.com/use-cases/

18. Business Problem
• Optimize walmart.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 of the 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 global bank
• 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 Nordic Telecom 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 largest hospitality / 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 shopping assistant
• 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

28. Bags

29. Men’s Backpack
Handbag

30. Use case: Knowledge Graphs

31. Use case: Fraud Analytics

32. Use case: Identity and Access Management

33. Use case: Master data management

34. Use case: Network and IT Operations

35. Use case: Real-time Recommendations

36. Use case: Social Networks

37. Use case: Graph-based AI & Analytics

38. Popular Graph Technology Use Cases for AI and Analytics

39. Customer stories on https://neo4j.com/customers/

40. Software
Financial
Services Teleco
m
Retail &
Consumer Goods
Media &
Entertainment Other Industries
Airbus

41. Fantastic Case Studies
from
GraphTour 2018

42. 42 https://www.slideshare.net/neo4j/volvo-cars-build-a-car-with-neo4j

43. 43
https://www.slideshare.net/neo4j/graphtour-previa-preventing-brun-outs-with-connected-health-care-data

44. 44
https://www.slideshare.net/neo4j/graphtour-madrid-running-neo4j-on-a-large-scale-image-platform

45. 45
https://www.slideshare.net/neo4j/graphtour-integrating-neo4j-in-ing-luxembourgs-environment

46. 46
https://www.slideshare.net/neo4j/graphtour-workday-tracking-activity-with-neo4j-english-version

47. 47
https://www.slideshare.net/neo4j/graphtour-crdit-agricole-making-the-most-of-public-information-on-our-clients

48. 48 https://www.slideshare.net/neo4j/graphtour-mastering-highly-distributed-architecture-with-neo4j

49. 49 https://www.slideshare.net/neo4j/decyphering-recipes-with-neo4j

50. 50
https://www.slideshare.net/neo4j/generali-fraud-analytics

51. 51
https://www.slideshare.net/neo4j/daimler-ag-structurecube-die-gklasse-im-sumpf-der-strukturen

52. IN SUMMARY!

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.

55. Questions?