GraphTour Europe 2019: Keynote GraphTour Europe 2019, Emil Eifrem, CEO & Co-Founder Neo4j

1. Emil Eifrem, CEO & Founder, Neo4j

2. Welcome!
#graphtour #neo4j

3. Agenda
• Graphs 101
• State of the Graph Union
• The Future of Graphs

4. Frederik Obermaier, Süddeutsche Zeitung, on the
importance of networks in journalism. From Panel at
Columbia University Feb 23, 2018.
“I’ve only come
across 3 or 4
stories in my
career that
weren’t about
networks.”

6. ACCOUNT
HAS
REGISTERED
ADDRESS
PERSON
IS_OFFICER_OF
PERSON
NAME
STREET
BANK
WITH
LIVES_AT
LIVES_AT
NAME
COMPANY
BANK
BAHAMAS
2.6 TB
11.5 million documents
Emails, Scanned Documents,
Bank Statements etc…

7. 2.6 TB
11.5 million documents
Emails, Scanned Documents,
Bank Statements etc… Person B
Bank US
Account
123
Person A
Acme Inc
Bank
Bahamas
Address X
HAS_ACCOUNT
REGISTERED
IS_OFFICER_OF
WITH
LIVES_AT
LIVES_AT
NODE
RELATIONSHIP

8. 2.6 TB
11.5 million documents
Emails, Scanned Documents,
Bank Statements etc…

12. ICIJ Pulitzer Price Winner 2017

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

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

15. “Forrester estimates that over
25% of enterprises will be using
graph databases by 2017.”
Forrester, 2014

16. Popularity of Graphs
DB-engines Ranking of Database Categories
• Graph DBMS
• Key-value stores
• Document stores
• Wide column store
• RDF stores
• Time stores
• Native XML DBMS
• Object oriented DBMS
• Multivalue DBMS
• Relational DBMS
Graph DB
2013 2014 2015 2016 2017 2018 2019

17. >50%of enterprises were using
graph databases
In 2017
Source: Forrester Vendor Landscape:
Graph Databases, October 6, 2017

18. Trend No. 5: Graph
…
The application of graph processing and graph DBMSs will grow at 100
percent annually through 2022 to continuously accelerate data
preparation and enable more complex and adaptive data science.
…
Graph analytics will grow in the next few years due to the need to ask
complex questions across complex data, which is not always
practical or even possible at scale using SQL queries.
https://www.gartner.com/en/newsroom/press-releases/2019-02-18-gartner-identifies-top-10-data-and-analytics-technolo
February 18, 2019

20. Retail
7 of top 10
Finance
20 of top 25 7 of top 10
Software
Hospitality
3 of top 5
Telco
4 of top 5
Airlines
3 of top 5
Logistics
3 of top 5
76%
FORTUNE 100
have adopted or
are piloting Neo4j

21. 2000+

22. News: Neo4j Startup Program Expansion
• Free access for startups with up to 50 employees;
under $3M in revenue
• Neo4j Enterprise Edition
• Neo4j Bloom
• Apply at http://neo4j.com/startup-program
• Notable alumni include:
Medium

24. News: Neo4j Startup Program Expansion
• Free access for startups with up to 50 employees;
under $3M in revenue
• Neo4j Enterprise Edition
• Neo4j Bloom
• Apply at http://neo4j.com/startup-program
• Notable alumni include:
Medium

25. AI & Graphs

26. EVIDENCE
BASED
MACHINE
LEARNING SYSTEMS
PRESCRIPTE
ANALYTICS
NATURAL LANGUAGE GENERATION
“Yankees”
“Giants”
“Penguins”
“Jets”
“Bears”
“Red Soxs”
NLP/TEXT MINING
PREDICITVE
ANALYTICS
RECOMMENDATION
ENGINES
DEEP
LEARNING

27. Graphs Provide Connections
& Context for AI

28. FATHER_OF DRIVE
WORKS_ATM
ARRIED_TO
PLAYS
WATCHES
BORN_IN

29. Knowledge Graphs

30. What Your ML Looks Like Today

31. Data Sources

32. Decisions
Machine Learning Pipeline
Data records
(“Features”)

36. “Increasingly we're learning that you can make
better predictions about people by getting
all the information from their friends and
their friends’ friends than you can from the
information you have about the person
themselves”
— Dr. James Fowler

37. Decisions
Machine Learning Pipeline
Data records

38. $
Better Decisions
Machine Learning Pipeline

39. Feature Extraction

40. Connected Feature Extraction

41. Four Pillars of Graph-Enhanced AI
1. Knowledge
Graphs
Context for Decisions
2. Connected
Feature Extraction
Context for Credibility
4. AI Explainability3. Graph
Accelerated AI
Context for Efficiency
Context for Accuracy

42. Thank You!
http://neo4j.com

43. @emileifrem #neo4j@emileifrem #neo4j