Rik Van Bruggen

1. Welcome to
Cedric Fauvet, cedric@neo4j.com
Rik Van Bruggen, rik@neo4j.com

2. 09:40-10:15 Introduction à la Plateforme de Graphes Neo4j - Cédric Fauvet, Business
Dévelopment France, Neo4j
10:15-11:00 Intégrer des flux de données dans Neo4j avec l'ETL Open Source Kettle - Matt Casters,
Chief Solutions Architect, Neo4j
11:00-11:15 Pause
11:15-12:00 Découverte de l'outil de visualisation Neo4j Bloom - Rik Van Bruggen, VP EMEA, Neo4j
Démo Bloom : Détection de fraude dans des transactions financières - Rik Van Bruggen, VP EMEA,
Neo4j
12:00-12:45 Calcul scientifique, data science, analyse de dépendance et base de données graphes -
Matthieu Quadrini, Product Owner - Thomas Serre, Responsable Technique & Denis Martin,
Architecte Système - Michelin
12:45-14:00 Déjeuner
Agenda AM

3. 12:45-14:00 Déjeuner
14:00-14:45 Détection & qualification d’événements Clientèle - Christophe Goset,
Agile CRM IT Manager - Crédit Agricole CIB
14:45-15:30 CAST IMAGING - Un IRM pour les systèmes IT complexes - Damien
Charlemagne, Group Product Manager - Cast Software
15:30-15:45 Pause
15:45-16:30 façons dont la technologie des graphes changent l'IA & le Machine
Learning - Benoît Simard, Consultant Neo4j
Agenda PM

4. 720+
7/10
20/25
7/10
53K+
100+
270+
450+
Adoption
Top Retail Firms
Top Financial Firms
Top Software Vendors
Customers Partners
• Creator of the Neo4j Graph Platform
• ~200 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 13M+ downloads & container pulls
• 270+ 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
Neo4j - The Graph Company

5. 2010 2011 2012 2013 2015 2017
Frustrated with
Gremlin, Neo
invented Cypher -
Leading language
for graph queries
First open
source GA
version of a
property graph
database
O’Reilly Graph
Database —
first definitive
book for graph
professionals
Introduced
labels to
simplify graph
modeling
openCypher.org
open sourced
Cypher query
language as de
facto standard
Industry’s
1st Graph
Platform
Graph Algorithms
for data scientists
Developer’s Neo4j
Desktop
2014
Visual Graph
Query Browser
2016
Causal
Consistency
for Graphs
Neo4j—The Graph Innovator
2018 2019
Morpheus
Graph is a
unique
paradigm
Neo4j Cloud
Neo4j Cloud EAP
Neo4j Bloom visual discovery
Cypher for Apache Spark
Cypher for Gremlin
GQL Manifesto

6. Then this happened...

7. Then this happened...

8. 09:40-10:15 Introduction à la Plateforme de Graphes Neo4j - Cédric Fauvet, Business
Dévelopment France, Neo4j
10:15-11:00 Intégrer des flux de données dans Neo4j avec l'ETL Open Source Kettle - Matt Casters,
Chief Solutions Architect, Neo4j
11:00-11:15 Pause
11:15-12:00 Découverte de l'outil de visualisation Neo4j Bloom - Rik Van Bruggen, VP EMEA, Neo4j
Démo Bloom : Détection de fraude dans des transactions financières - Rik Van Bruggen, VP EMEA,
Neo4j
12:00-12:45 Calcul scientifique, data science, analyse de dépendance et base de données graphes -
Matthieu Quadrini, Product Owner - Thomas Serre, Responsable Technique & Denis Martin,
Architecte Système - Michelin
12:45-14:00 Déjeuner
Agenda AM

9. Graphs are
BLOOMING
Rik Van Bruggen, rik@neo4j.com
@rvanbruggen
blog.bruggen.com

10. Neo4j is an enterprise-grade native graph platform that enables you to:
• Store, reveal and query data relationships
• Traverse and analyze any levels of depth in real-time
• Add context and connect new data on the fly
10
Who We Are: The Graph Platform
• Performance
• ACID Transactions
• Schema-free Agility
• Graph Algorithms
Designed, built and tested natively
for graphs from the start for:
• Developer Productivity
• Hardware Efficiency
• Global Scale
• Graph Adoption
Graph
Transactions
Graph
Analytics
Data Integration
Development
& Admin
Analytics
Tooling
Drivers & APIs Discovery & Visualization

11. Conceive &
Visualize
Code
Compute
Store
Non-Native Graph DBNative Graph DB RDBMS
Optimized for graph workloads
Connectedness Differentiates Neo4j

12. Collections-Focused
Multi-Model, Documents, Columns
& Simple Tables, Joins
Neo4j is designed for data relationships
Different Paradigms
NoSQL
Relational
DBMS
Neo4j Graph
Platform
Connections-Focused
Focused on
Data Relationships
Development Benefits
Easy model maintenance
Easy query
Deployment Benefits
Ultra high performance
Minimal resource usage

13. "Neo4j continues to
dominate the graph
database market.”
“69% of enterprises
have, or are planning
to implement graphs
over next 12 months”
October, 2017
“The most widely stated
reason in the survey for
selecting Neo4j was
to drive innovation”
February, 2018
Critical Capabilities for
DBMSA
“In fact, the rapid rise of
Neo4j and other graph
technologies may signal
that data connectedness
is indeed a separate
paradigm from the model
consolidation happening
across the rest of the
NoSQL landscape.”
March, 2018
Graph is a Unique Paradigm

14. Density Drives Value In Graphs
Metcalfe’s Law of the Network (V~n2)
5 hops < less Value
100’s of hops deliver
immense VALUE

15. 15
Graph
Transactions
Graph
Analytics
Data Integration
Development
& Admin
Analytics
Tooling
Drivers & APIs Discovery & Visualization
Developers
Admins
Applications Business Users
Data Analysts
Data Scientists
Enterprise Data Hub

16. Neo4j Bloom
16

17. Context
Millenia of associative thinking
Centuries of advanced math
subjects
Decades of ER diagrams
YEARS of whiteboard drawings

18. Neo4j - the company

19. As a thinking tool, to visually organize information
As a development tool, for working with graph data
As a communication tool, for describing what is in the graph
As an interactive tool, for exploring data relationships
As a reporting tool, for summarizing business information
As an analysis tool, for revealing critical trends,
influences and discrepancies
How is graph visualization useful?

20. 20
Popular Visualization Options for Neo4j
Neo4j Bloom
Provided by Neo4j
Exclusively optimized for Neo4j
graphs
Deploys easily in Neo4j
Desktop
Focused on graph exploration
thru a code-free UI
Currently caters to data
analysts and graph SMEs
Currently for individual or small
team use
Viz Toolkits
3rd party e.g. vis.js, d3.js,
Keylines
Some offer data hooks into
Neo4j, others may require
custom integration
Offer robust APIs for flexible
control of the viz output
Cater to developers who will
create a custom solution, usually
with limited interactivity
Departmental, enterprise or
public use
BI Tools
3rd party e.g. Tableau, Qlik
Not optimized for graph data,
may require a special
connector
UI for dashboard and report
creation with many kinds of viz,
in addition to graph viz
Cater to business users and
data analysts
Departmental, cross-
department or enterprise use
Graph Viz Solutions
3rd party e.g. Linkurious,
Tom Sawyer
Support Neo4j and other
graph / RDF sources
Feature UI for exploration or
APIs for customizing output
and embedding/publishing
Solutions may cater to
business users, analysts or
developers
Small team, departmental or
cross-department use
Little technical expertise Most technically involved
Most exploration friendly Most consumption friendly
Smaller deployments Larger deployments

21. Perspective
Visualization
Exploration
Inspection
Editing
Search
21
Business view of the graph
Departmental views • Hiding PII • Styling
GPU Accelerated Visualization
High performance
physics & rendering
Direct graph interactions
Select, expand, dismiss, find paths
Node + Relationship details
Browse from neighbor to neighbor
Create, Edit, Delete
Code-free graph changes
Near-natural Language Search
Full-text search • Graph patterns
• Custom Search Phrases
Neo4j Bloom
Features
bloom

22. • High fidelity
• Scene navigation
• Property views
• NLP Search
• Search suggestions
• Saved phrase history
• Property editor
• Schema Perspectives
• Bloom chart type
Neo4j Bloom
22
Communicate, discover, visualize, isolate
and navigate

23. Neo4j Bloom User Interface
23
• Prompted Search
• Property Browser &
editor
• Category icons and
color scheme
• Pan, Zoom & Select

24. Graph Perspective
24
Manage visibility and reduce
clutter, revealing the right
information to the right users.
• Selective Property Visibility
• Selective Relationships
• Defined Entity Patterns*
Need-to-know Details
• Departmental Views
• Hide Personal Ident Info
• Structural-only Dev view
Rich Entities*
• Truck with Packages
• Person with Aliases
• Blog Post with Comments
• Component with Parts

25. Graph Search
25
Ask Bloom what you’re looking
for using idiomatic phrases
based on the graph structure
and content.
• Search Everywhere
• Find Graph Patterns
• Customize Search Phrases
LET’S TAKE
A LOOK!

26. Find Fraud Rings
MATCH
(accountHolder:AccountHolder)-[]-
>(contactInformation)
WITH contactInformation,
count(accountHolder) AS RingSize ,
collect(id(accountHolder)) AS
_FraudRing
WHERE RingSize > 1
MATCH (contactInformation)<-[]-
(accountHolder2:AccountHolder) ,
(accountHolder2)-
[r:HAS_CREDITCARD|HAS_UNSECU
REDLOAN|HAS_SSN]-
>(unsecuredAccount)
WITH collect(id(accountHolder2))
AS AccountHolders ,
contactInformation , RingSize ,
_FraudRing , TOFLOAT(SUM(CASE
type(r)
WHEN 'HAS_CREDITCARD' THEN
unsecuredAccount.limit
WHEN 'HAS_UNSECUREDLOAN'
THEN unsecuredAccount.balance ELSE
0 END)) as FinancialRisk
Match (ah:AccountHolder)-[r]-(conn)
where id(ah) in _FraudRing
RETURN ah,r,conn
limit 20

27. Find card skimmers
MATCH (p:Purchase)-
[:WITH_CARD]->(bc)<-
[:WITH_CARD]-(p2:Purchase)
WHERE p2.time > (p.time - (1 *
60000)) AND p2.time < (p.time + (1
* 60000))
WITH bc, [p ,p2] as pur
UNWIND pur as prs
MATCH (bc)<-[:WITH_CARD]-(prs)-
[:FROM_IP]->(ip:IP)-
[:LOCATED_IN]->(s:State)
WITH bc , collect(distinct (s.name))
as states , collect(distinct (ip.ip)) as
ips , count(distinct (prs)) as
purChaseCount , sum(distinct
(prs.amount)) as purChaseTotal ,
collect(distinct (id(prs))) as _purids
WHERE size(ips) > 1
MATCH path = (bc)-[r*..2]-()
RETURN path
limit 10

28. Transfers above XXXX
Match (n:MoneyTransfer)-[r]-(conn)
where n.amount > $param
return n, r, conn

29. Top XXX money transfers
match (mt:MoneyTransfer)
with mt
order by mt.amount desc
limit $param
Match path = ((mt)-[*..2]-(conn))
return path

30. Links between Accountholders
match (a1:AccountHolder {firstName:
$param1}),
(a2:AccountHolder {firstName: $param2}),
path = shortestpath ((a1)-[*..20]-(a2))
return path

31. Neo4j Bloom Q&A
31

32. Questions?
Answers!