This document contains an agenda and presentation slides for a Neo4j Graphs in Government event. The presentation introduces graph databases and Neo4j, discusses how graphs can help solve network-oriented problems, provides examples of graph use cases in various industries, and highlights new features in Neo4j 4.0 like easy management, unlimited scaling, and granular security. Case studies demonstrate how Neo4j has helped organizations like the US Army, MITRE, Adobe, and the German Center for Diabetes Research tackle complex data challenges.

1. Lance Walter, CMO, Neo4j
Neo4j Graphs in Government Day
March 5, 2020

2. Welcome!
#graphtour #neo4j

3. Strictly ConfidentialStrictly Confidential
• Agenda Review
• Overview: Connected data and graphs
• Market landscape
• Neo4j Introduction
• Case studies
• What’s next in graphs?
• Wrap-up
Topics

4. Today’s Agenda

5. Networks of People Business Processes Knowledge Networks
E.g., Risk management, Citizen
Service, Payments
E.g., Employees, Citizens,
Suppliers, Partners,
Influencers
E.g., Enterprise content,
Domain specific content,
eCommerce content
Data connections are increasing as rapidly as data volumes
The Rise of Connections in Data

6. Graphs have been universally recognized as a great solution
for specific types of problems
- Graph Problems -
and
recognition is GROWING!

7. Look at this data…
Element Depends On
A B
A C
A D
C H
D J
E F
E G
F J
G L
H I
J N
J M
L M

8. Element Depends On
A B
A C
A D
C H
D J
E F
E G
F J
G L
H I
J N
J M
L M
Time challenge #1: What if J fails?
?

9. Look at this data again…

10. If your business problem has a lot of dependencies - which in IT /
database terms are represented by JOINs between different entities -
and if solving for these dependencies in near real time is important
to you, then your problem is probably easiest solved with graph
technology - and we can safely call it a
GRAPH PROBLEM.
Identifying Graph Problems

11. 2.6 TB
11.5 million documents
Emails, Scanned Documents,
Bank Statements etc…
The Graph Problem at Scale: Panama
Papers

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

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

16. Strictly Confidential
16
Graph is a Top Technology Trend for 2020

17. “Choice (from 3:00 to 6:00), during
which the DBMS technology asset
class typically moves from
adolescent status into the early
mainstream. This is the phase of
highest growth in demand (market
penetration potentially reaches
50%), during which supply options
should grow…”
17
Graphs in the Early Mainstream

18. Making Graph Database Market History:
An Emerging Open Standard

20. Neo4j Company Update

21. A Vibrant
Growing
Community

22. A Vibrant
Growing
Community
50%
1000+
Sign ups for Startup Program

23. A Vibrant
Growing
Community
60+Events
6Continents
Global Graph Day

24. A Vibrant
Growing
Community
r.neo4j.com/twin4j

25. Neo4j is one
of the Fastest
Growing Skills

26. 76%FORTUNE
100
have adopted
or are piloting
Neo4jFinance
20 of top 25
7 of top 10
Software
Retail
7 of top 10
Airline
s
3 of top 5
Logistic
s
3 of top 5
Telco
4 of top 5
Hospitalit
y
3 of top 5
Growing
Adoption
in the
Enterprise

27. Case Studies

28. Background
• US IT consulting firm helped US Army streamline
equipment deployments and maintenance spending
• Saving lives by improving the operational readiness
of Army equipment like tanks, radios, transports,
aircraft, weaponry, etc.
Business Problem
• Needed to modernize procurement, budget and
logistics processes for equipment & spare parts
• Millions of connections among a tank’s bill-of-
materials, for example
• Improve “what if” cost calculations when planning
missions and troop deployments
• Mainframe systems required over 60 man-hrs to
calculate changes… planning took too long.
Solution and Benefits
• 118M nodes & 185M relationships
• Shed cost estimation times by 88%
• Improved parts delivery timing and accuracy
• DBA labor required dropped by 77%
• Equipment TCO more predictable
• Safer soldiers
US Army / Calibre Systems Equipment Logistics
Parts Assembly & Equipment Maintenance28

29. Background
• The MITRE Corporation is a federally-funded, not-
for-profit company that manages cybersecurity for
seven national research and development
laboratories around the United States including the
Center for National Security
• Founded in 1958, engaged in numerous public-
private partnerships as well as independent
research
Problem
• Constantly-evolving networks – devices,
configurations
• Huge volumes of “noise” from virus warnings to
failed logins
• Isolated datapoints with no context to separate the
most serious threats from the benign
• Existing database could not provide the context or
performance to manage a real-time environment
Solution and Benefits
• CyGraph - Agencies now have scalable,
comprehensive analytic and visualization capabilities
• Allowed agencies to capture a picture of their
cybersecurity environment that connects previously
isolated data points
Mitre Cybersecurity for Federal Agencies
29
“CyGraph’s comprehensive knowledge base tells
a much more complete story than that of basic
attack graphs or mission dependency models. [It]
includes potential attack-pattern relationships that
fill in gaps between known vulnerabilities and
threat indicators.”
- Steven Noel, Principal Cybersecurity
Engineer

30. Background
• Social network of 10M graphic artists
• Peer-to-peer evaluation of art and works-in-progress
• Job sourcing site for creatives
• Massive, millions of updates (reads & writes) to Activity
Feed
• 150 Mongos to 48 Cassandras to 3 Neo4j’s!
Business Problem
• Artists subscribe, appreciate and curate “galleries” of
works of their own and from other artists
• Activities Feed is how everyone receives updates
• 1st implementation was 150 MongoDB instances
• 2nd implementation shrunk to 48 Cassandras, but it
was still too slow and required heavy IT overhead
Solution and Benefits
• 3rd implementation shrunk to 3 Neo4j instances
• Saved over $500k in annual AWS fees
• Reduced data footprint from 50TB to 40GB
• Significantly easier to introduce new features like,
“New projects in you Network”
Adobe Behance Social Network of 10M Graphic Artists
Social Network30
EE Customer since 2016 Q

31. Background
• Over 7M citizens suffer from Diabetes
• Connecting over 400 researchers
• Incorporates over 50 databases, 100k’s of Excel
workbooks, 30 database of biological samples
• Sought to examine disease from as many angles as
possible.
Business Problem
• Genes are connected by proteins or to metabolites,
and patients are connected with their diets, etc…
• Needed to improve the utilization of immensely
technical data
• Needed to cater to doctors and researchers with
simple navigation, communication and connections
of the graph.
Solution and Benefits
• Dr. Alexander Jarasch, Head of Bioinformatics and
Data Management
• Scientists can conduct parallel research without asking
the same questions or repeating tests
• Built views like a liver sample knowledge graph
DZD - German Center for Diabetes Research
Medical Genomic Research31
EE Customer since 2016 Q

32. Looking Forward:
AI and Graphs

33. 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

34. • For AI to be more situationally appropriate &
"learn" in a way that leverages adjacency to
understand and refine outputs, it needs to be
underpinned by context.
• AI standards that don't explicitly include contextual
information result in subpar outcomes
• Narrowly focused and rigid AI,
uninterpretable predictions, and less
accountability
• Graph technologies are a state-of-the-art,
purpose-built method for adding and leveraging
context from data.
• Graph technology is a powerful foundation for AI
34
Neo4j Response to NIST Call for Information on
AI Standards
https://www.nist.gov/system/files/docu
ments/2019/06/03/nist-ai-rfi-
neo4j_001.pdf

35. Neo4j 4.0

36. By Developers
For Developers
80+% of our customers
start as individual developers
I’ve been playing with @neo4j today and I must say, even though I’ve only
about scratched the surface of it, I love it. And about Cypher: I can’t
believe how much sense it makes and how easy I got started writing
queries. Plus the Desktop app was a very pleasant experience.
After learning Neo4j, it’s amazing to me how much better a graph data
structure suits real-world relationship models. Bye bye tricky SQL joins!
Good god @neo4j's intro console with the movie example is literally the
best database engine intro I have ever seen <applause>

37. The Six Pillars of the Neo4j Database

38. What do you
want?

39. Here's what
we've heard Build Faster Scale Bigger Launch EasierBe More Secure

40. What’s New
in Neo4j 4.0 Easy
Management
Unlimited Scale Granular security Fast to develop

41. What’s New
in Neo4j 4.0 Multi-DatabaseNeo4j Fabric
Schema-Based
Security
Reactive
Database

42. Wrap Up

43. Thank You to Our Sponsors!

44. #neo4j@lancewalter #neo4j