We live in an era where the world is more connected than ever before and the trajectory is such that data relationships will only continue to increase with no signs of slowing down. Connected data is the key to your business succeeding and growing in today’s connected world. Leading enterprises will be the ones that utilize relationship-centric technologies to leverage connections from their internal operations and supply chain to their customer and user interactions. This ability to utilize connected data to understand all the nuanced relationships within their organization will propel them forward as they act on more holistic insights. Every organization needs a knowledge graph because connected data is an essential foundation to advancing business. Additional reading on connected can be found here: https://www.graphgrid.com/why-connected-data-is-more-useful/

1. Knowledge Graphs
for a Connected World
March 24, 2016
Benjamin Nussbaum
@bennussbaum
www.graphgrid.com | www.atomrain.com

2. Introduction
Benjamin Nussbaum
20 years of Technology Innovation.
Software architecture | Database design | Server infrastructure
President & CTO of AtomRain,
one of the world’s leading NEO4J Solution Partners
and makers of GraphGrid.
a platform by

3. Today’s Meetup Agenda
Knowledge Graphs for a Connected World
• What is driving the adoption of graphs
Graph Basics for AI Champions
• Where a graph fits within a web 3.0 strategy
• Why a graph is the first step to AI
• How a graph works
Graph Development for Innovation Teams
• Who does what
Graphs in Action
• Popular use cases
• Putting it all together
Q&A

4. A Web of Things
Generating a Web of Data
Knowledge Graphs
are driving
strategies for
Web 3.0,
The Semantic Web

5. A Web of Things
Generating a Web of Data
Dynamic Data
At Web Scale
The Entertainment Graph TM
560 million nodes
1.8 billion relationships
3.0 billion properties
Continuous ingestion from dozens of
external such as Wikipedia, Netflix, Amazon
and iTunes for personalized recommendations
and social discovery of content.
The World’s Leading Graph Database

6. Brands and Ventures
now have access to graph platform services
Solution Partner

7. Brands and Ventures
now have access to graph development partners
Solution Partner

8. Today’s Meetup Agenda
Knowledge Graphs for a Connected World
• What is driving the adoption of graphs
Graph Basics for AI Champions
• Where a graph fits within a web 3.0 strategy
• Why a graph is the first step to AI
• How a graph works
Graph Development for Innovation Teams
• Who does what
Graphs in Action
• Popular use cases
• Putting it all together
Q&A

9. Knowledge
Graph
Big Data
Ingestion
Real-Time
Queries & Algorithms
Pre-Computed
Queries & Algorithm
Discovery
+ Reasoning
Personalizing Apps Smart Places Interacting Machines
Your Graph is a Data Service to “Smart” Touchpoints
DATA PLATFORM API

10. Data
Science
Artificial
Intelligence
Relating
with Interaction
Acting
with Processing Layers
Serving
with Graphs
Discerning
with Patterns
Identify Link Prescribe Do ThinkPredict Sense Adapt
Apps
access and update
the graph
Real-Time
data about customers
things, and relationships.
Algorithms
reason
over the graph
Patterns
for best, worst, and next
steps or things.
Smart Things
send machine results
to the graph
History
of a machine’s
action and results.
AIs
access customer
insight
in the graph
Prediction
of a customer’s
next need or want.
A Graph Manages
your Brand’s Evolving Knowledge
Knowledge Graph

11. A Graph Records a New Kind of Data
Semantic Web
and
Knowledge Graphs
Enterprises Systems
and
Business Transactions
For Business Operations
▪ Business Systems
generate data.
▪ Data about Business
Orders, purchases, invoices,
customer interactions…
▪ Static System of Record
Standard data; relationships are
not first class citizens.
CRM
System
Product
Catalog
Invoice
System
▪ Connected Customers & Smart
Things
generate data.
▪ Data about Real-World
Concepts, people, places, things,
and their relationships.
▪ Dynamic Graph of Relationships
Discovers and learns through
patterns as relationships change
For Connected Experiences

12. A “Node”
in the graph
Hotel
Room
Person
A Graph Models
Real-World People, Places, and Things
Solution Partner
A “Label”
in the graph

13. A “Relationship”
in the graph
PREFERS
Hotel
Room
Person
HAS_AVAILABLE
A Graph Models
Contextual Relationships
Solution Partner

14. PREFERS
Hotel
Room
Person
“Properties”
in the graph
lastStayed: 2-10-2015
name: Hilton Hotel
name: Jane Smith
number: 315
HAS_AVAILABLE
A Graph Stores and Updates Data
about Each Thing and its Relationships
Solution Partner

15. PREFERS
Hotel
Room
Person
Queries
traverse the graph to discover
relevant resources
For Jane’s preferred hotel
and travel destination,
identify available rooms,
present information to her app. HAS_AVAILABLE
Algorithms
calculate to
solve problems
- Spot Patterns.
- Prescribe Best Solution.
- Predict Results.
Queries and Algorithms
Reason over the Graph
Solution Partner

16. Graph Queries
Start with one “entity” and traverse the graph
to discover linked people, places, or things
Query for a Graph
MATCH (boss)-[:MANAGES*0..3]->(sub),
(sub)-[:MANAGES*1..3]->(report)
WHERE boss.name = “John Doe”
RETURN sub.name AS Subordinate,
count(report) AS Total
NEO4J Cypher Language
“Complex Join” in SQL
Solution Partner

17. Example:
Calculates the shortest path—the least number of nodes, relationships—between two nodes
Traversal Algorithms
Navigate the graph and calculate to spot patterns or solve problems
Solution Partner

18. Today’s Meetup Agenda
Knowledge Graphs for a Connected World
• What is driving the adoption of graphs
Graph Basics for AI Champions
• Where a graph fits within a web 3.0 strategy
• Why a graph is the first step to AI
• How a graph works
Graph Development for Innovation Teams
• Who does what
Graphs in Action
• Popular use cases
• Putting it all together
Q&A

19. Subject Matter Experts work with Graph Experts
to create the conceptual model

20. Graph Software Engineers
create the software solution to transform and load data into the graph model

21. Multidisciplinary Team
ensures the quality of queries and algorithms
User Results
Ongoing Lab:
• Subject Matter Experts
(i.e Marketing)
• Data Engineer
• Algorithm Developer

22. Knowledge
Graph
Big Data
Ingestion
Real-Time
Queries & Algorithms
Pre-Computed
Queries & Algorithm
Discovery
+ Reasoning
DATA PLATFORM
Platform Experts
manage the scaling platform
Top Challenges
1. Query Performance
2. Algorithm Performance
3. Graph Operation
at Scale
4. Server Infrastructure
at Scale
5. Ingestion Engines
6. Entity Resolution
API
An enterprise-grade, internet scale
data management platform

23. Today’s Meetup Agenda
Knowledge Graphs for a Connected World
• What is driving the adoption of graphs
Graph Basics for AI Champions
• Where a graph fits within a web 3.0 strategy
• Why a graph is the first step to AI
• How a graph works
Graph Development for Innovation Teams
• Who does what
Graphs in Action
• Popular use cases
• Putting it all together
Q&A

24. Master Data Management
For customer interests, product lines, store locations, org charts…
For white papers, visit neo4j.com/use-cases/

25. Identify & Access Management
Validates who you are, what group you belong to, and what you’re permitted to
do.
For white papers, visit neo4j.com/use-cases/

26. Graph Based Search
Delivers a structured result: such as a song, music attributes, artist, album, and
playlists.
For white papers, visit neo4j.com/use-cases/

27. Real time Recommendations
Based on past purchases, recent browsing, or friends’ purchases.
For white papers, visit neo4j.com/use-cases/

28. Social Network
Family, friend and follower relationships
reveal influencers, peer groups, and patterns of social behavior.
For white papers, visit neo4j.com/use-cases/

29. Fraud Detection
Uncovers fraud rings and patterns of unusual customer behavior.
For white papers, visit neo4j.com/use-cases/

30. Putting it all together: A Connected Fitness Venture
PERSONA
GOALS AND PREFERENCES
• Skill Level
• Health Conditions
• Workout Goals
• Eating Goals
• Muscle Groups
• Body Areas
• Workout Types
• Supplement Needs
CONSUMER WANTS
1. What fitness programs are best to help me accomplish my workout goals?
2. Which nutritional supplements will help me achieve my eating and workout goals?
3. Who in the community can I work out with and which workout would be good to do
together?
Scoring Algorithm
considers importances
the user places
on each item
For Complete Review with Sample Queries
http://neo4j.com/graphgist/95f4f165-0172-4b3d-981b-edcbab2e0a4b

31. BRAND’s
WEB OF EVERYTHING
• Supplement lines
• Fitness programs
• Social network
Putting it all together: A Connected Fitness Venture
For Complete Review with Sample Queries
http://neo4j.com/graphgist/95f4f165-0172-4b3d-981b-edcbab2e0a4b

32. Product Cross-Selling
aligned to users’
personal goals—and results
Putting it all together: A Connected Fitness Venture
For Complete Review with Sample Queries
http://neo4j.com/graphgist/95f4f165-0172-4b3d-981b-edcbab2e0a4b

33. Today’s Meetup Agenda
Knowledge Graphs for a Connected World
• What is driving the adoption of graphs
Graph Basics for AI Champions
• Where a graph fits within a web 3.0 strategy
• Why a graph is the first step to AI
• How a graph works
Graph Development for Innovation Teams
• Who does what
Graphs in Action
• Popular use cases
• Putting it all together
Q&A

34. Q&A
What do you think about Graphs?

35. Thank You!
Knowledge Graphs for a Connected World
March 24, 2016
Benjamin Nussbaum
@bennussbaum
www.graphgrid.com | www.atomrain.com