Keynote: Art of the Possible - Chandra Rangan

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The Art of the
Possible with
Graph Technology

2
Chandra
Rangan
Chief Marketing Officer

© 2023 Neo4j, Inc. All rights reserved.
3
Business challenges = data challenges

4
Image showing case study goes here
Placeholder
CATERPILLAR
Unlocking insights for
efficient equipment
repair and maintenance
across tens of millions
of technical documents
was an enormous
challenge for
Caterpillar

5
At the heart of every enterprise challenge
is an explosion of data complexity

6
ACROSS ALL INDUSTRIES
Hästens
Customer 360 strategy and
ecommerce modernization
PwC
Rapid fraud and anti-money
laundering detection
Adobe
World’s largest social network
for professionals & creatives

7 © 2023 Neo4j, Inc. All rights reserved.
DATA GROWTH IS ACCELERATING.
EVERYONE IS CONNECTED TO EVERYTHING
200+
Zettabytes
In cloud data storage
by 2025
65
Average number of
enterprise SaaS apps
41B
Connected IOT
devices by 2025

8
Organizations are drowning in data
but lacking in insight

9
80% of business leaders
say data is critical in
decision-making, yet
41% cite a lack of
understanding of data
because it is too
complex or not
accessible enough
- Salesforce Global Survey, 2023

Data silos
hide valuable
context
THE CHALLENGE

11
TODAY’S REALITY
Connections
in data are as
valuable as the
data itself

CONNECTION COMPLEXITY
How do you navigate this data
explosion at scale?

13
Legacy
systems
can’t keep up
“Relational” Databases
don’t handle relationships well
NoSQL Databases
don’t handle relationships at all

14
A fundamentally new approach is needed

15
Data, meet Graph.

Graph creates a
more intuitive and
connected view of
data relationships,
unlocking deeper
insights and context

17
THE FASTEST GROWING DATABASE CATEGORY FOR 10 YEARS

18
Graph enables organizations to quickly and easily
uncover hidden relationships and patterns
across billions of data connections
Powering applications that are
impossible with other technologies

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THE PROPERTY GRAPH: SIMPLY POWERFUL
Employee City
Company
Nodes represent
objects (nouns)
Relationships are directional
Relationships connect nodes are
represent actions (verbs)
Relationships can have
properties (name/value pairs)
Nodes can have
properties (name/value
pairs)
name: Amy Peters
date_of_birth: 1984-03-01
employee_ID: 1
:HAS_CEO
start_date: 2008-01-20
:LOCATED_IN

QUERY PERFORMANCE AS # OF JOINS INCREASE
Connectedness and Size of Data Set
Response
Time
Relational and
other NoSQL
databases
Native Graph Database
1000x Advantage
Minutes to milliseconds
5+ hops
3+ degrees
Thousands of connections
0 to 2 hops
0 to 3 degrees
Few connections

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SOLVING DATA COMPLEXITY
Graph powers the next generation of enterprise data applications
Hästens
Reducing delivery times
and driving revenue growth.
Caterpillar
Enabling efficient equipment
repair and maintenance.
Adobe
Reduced data footprint and
millions saved in cloud fees.
PwC
Next-generation fraud and
money laundering detection.

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By 2025, graph will be
used in 80% of data and
analytics innovations

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Neo4j means Graph

Our Mission
Help the world
make sense of data
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Emil Eifrem
Founder & CEO

NEO4J
The first-ever
graph database
Creator of the
market category
Continued market
leader
The Forrester WaveTM
For Graph Data Platforms, Q4 2020

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FUELING DISCOVERY AND TRANSFORMATION IN EVERY FIELD
Real-Time
Recommendations
Fraud
Detection
Network &
IT Operations
Master Data
Management
Identity & Access
Management
Risk &
Compliance

20 / 20
Top US banks
3 / 5
Top Aircraft Manufacturers
7 / 10
Top Telcos
3 / 5
Top Hotel Groups
8 / 10
Top Insurance Companies
10 /10
Top Automakers
7 / 10
Top Retailers
5 / 5
Top Pharmaceuticals
Trusted by
75 of the

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LOVED BY CUSTOMERS
Easy implementation
“Best in a class, easy to
implement, and greatly
beneficial for our business.”
- Director, $3B-10B company
“Most human-friendly
Cypher dev language
with one of the best
integration capabilities”
Developer friendly Speed to insight
“What used to take weeks
or months, we now get
answers to in minutes or
even seconds.” – Jonathan L.
Community

HUGE INTEREST IN GRAPH FUELED BY AI & ML
“50% of Gartner
inquiries on the topic
of AI involve discussion
of the use of graph
technology.”
35x increase in AI research papers
featuring Graph over the past decade
Source: Dimensions Knowledge System
365
13,040

GRAPH DATA SCIENCE:
MAKE SENSE OF DATA RELATIONSHIPS
Machine Learning Pipeline
Pl
ay
s
Lives_in
In_sport
Likes
F
a
n
_
o
f
Plays_for
K
n
o
w
s
Knows
Knows
K
n
o
w
s
Explore the hidden patterns and features in your data
What’s important? What’s unusual? What’s next?

BETTER BUSINESS OUTCOMES
WITH THE DATA YOU ALREADY HAVE
Complex joins operations
Mining multiple tables
Brute force comparisons
Fractured data
Tedious manual
approximations
Removes complexity
and eliminates pain

Optimizes Data Science
workflows
Fractured data
Tedious manual
approximations
95% reduction in Machine
Learning computation time
Up to 500x faster than open
source libraries
Removes complexity
and eliminates pain
🏎
🏎

Optimizes Data Science
workflows
Fractured data
Tedious manual
approximations
Up to 30% improvement
in model performance
3x better churn predictability
5x reduction in factory
production lead time
600% improvement in traﬃc
$5 million of additional fraud
cases detected
95% reduction in Machine
Learning computation time
Up to 500x faster than open
source libraries
Improves business
outcomes
Removes complexity
and eliminates pain
🏎
🏎

GRAPH DATA SCIENCE:
IMPROVE MODELS & ANSWER BIG QUESTIONS
Pathfinding
& Search
Centrality Community
Detection
Machine
Learning
Link
Prediction
Similarity Embeddings And more …
Over 65 pretuned, parallelized algorithms. Iterate fast with different data sets,
models, and version trained models.
Bring the DNA of your graph into a
format that other pipelines can ingest.
The Largest Catalog of
Graph Algorithms
Native Graph Catalog and
Analytics Workspace
Graph Embeddings for
Machine Learning

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GRAPH DATA SCIENCE MATURITY MODEL
Knowledge Graphs
Graph Algorithms
Graph Native ML
Find the patterns you’re
looking for in connected data
Identify associations,
anomalies, and trends using
unsupervised machine learning
Learn features in your graph
that you don’t even know
are important yet
→
→

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Neo4j Graph Database & Analytics
The future of enterprise data applications

37
N E W Y O R K

Keynote: Art of the Possible - Chandra Rangan

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