5. 5
Neo4j PS Professional Services Offer
Training &
Enablement
Solution Delivery
and Management
Packaged Services
Typically 5-25 days
Neo4j advises
Customer builds
80% of engagements
Custom Scoped
50+ days
Neo4j delivers
Customer supports
20% of engagements
6. PROFESSIONAL
SERVICES
GRAPH ACADEMY
SOLUTIONS
CUSTOMER SUPPORT
● Packaged Services
● Staff Augmentation
● Project/Solution Delivery
● Class room training
● Online/Virtual training
● Certification
● Innovation Labs
● Solution Workshops
● Solutions Development
●24x7x365 & KB
●Platinum support
●Cloud Managed Services
●DBaas (NEW)
●Agile Solution Support
Training
Enablement
Solution Delivery
and Mgmt
Organisation and offerings
10. „… an IT solution is an aggregation of products and
services, as opposed to a single, discrete product ...
which helps to solve a particular problem“
https://searchitchannel.techtarget.com/definition/solution
10
What is an IT Solution?
15. Solution (Foundation) Framework
Neo4j Graph Platform
Recom
Framework
Custom
App
Solution Foundation Framework
Neo4j Data Orchestrator Framework
Neo4j Deployment Framework Neo4j Managed Service
Fraud
Framework
Network Mgmt
Framework
Custom
App
Custom
App
Custom
App
Custom
App
Custom
App
Neo4j Version Management Service
16. Solution (Foundation) Framework
Neo4j Graph Platform
Recom Telco
App
Solution Foundation
Framework
Development &
Administration
Analytics
Tooling
Graph
Analytics
Graph
Transactions
Data Integration
Discovery & VisualizationDrivers
App App
17. Solution (Foundation) Framework
Neo4j Graph Platform
Recom Telco
App
Solution Foundation
Framework
Development &
Administration
Analytics
Tooling
Graph
Analytics
Graph
Transactions
Data Integration
Discovery & VisualizationDrivers
App App
API dev
3rd party
graph viz
Custom dev -
graph viz libraries
3rd party
analytics
Python,
Java ML, ...
Kettle
3rd party
DI/EAI
Docker
Kubernetes
Git
Lineage
Kettle
18. UI /GRAND stack
API Layer
Neo4j Data Orchestrator
APOC
Trigge
r
Bloom
Apollo Client
ReactJS (
ReactGraphVis)
VisJS
Dashboards
Business Logic (JS)
Neo4j Graph Server
Apollo
Business Logic (Server) Cypher
29. Where AI and ML fit in
29
Development &
Administration
Analytics
Tooling
Graph
Analytics
Graph
Transactions
Data Integration
Discovery & VisualizationDrivers & APIs
AI
30. Differences between ML and Analytics
30
Machine learning:
• Determine domain parameters
• Historical-based discoveries
• Learn and improve without explicit
programming
31. Graph analytics:
• Uses inherent graph structures
• Uncover real-world networks
through their connections
• Forecast complex network
behavior and identify action
Differences between ML and Analytics
32. Today challenges with Machine Learning:
• Doesn’t take multiple relationship hops into account
• Takes time to iteratively train a model
• Computational inefficiency of connecting data
Benefits of Mixing Graph Analytics with ML
Graphs bring:
• Context to machine learning
• Feature filtration
• Connected feature extraction
33. Neo4j has an ‘out of the box’ Graph Algorithms plugin:
• Path finding and Search
• Centrality and Importance
• Community Detection
• Similarity and Machine Learning Workflow
Many different ways to work with your ML algorithms in Neo4j:
• Support for many languages (Python, .Net, Java, Go, Ruby, etc.)
• Different data integration options
• Triggers, event-driven architecture, user-defined functions
34
Working with Graph Analytics and ML
34. Knowledge graph example:
• Using topic finding ML processes
(e.g. Latent Dirichlet Allocation)
• Feeding the output into a graph database
• Search for topics, find related concepts, etc.
35
Graph and Machine Learning Examples
Recommendation engine example:
• Use ML processes such as collaborative filtering
• Enrich graph with the output
• Use graph as feedback for future iterations
35. IoT/Connected Home:
• Master Data Management
• Entity resolution using
community detection and
similarity
Customer Experience Management:
• Customer journey path analysis
(path finding)
36
Graph Analytics and Algorithm Examples
36
CONNECTS
CONNECTS
C
O
N
N
EC
T
S
RUNS_ON
CONNECTS
RUNS_ON
CONNECTSC
O
N
N
EC
TS
CONNECTS
RUNS_ON
RUNS_ON
RUNS_ONC
O
N
N
EC
TS
ZONE
ZONE
ZONE
DEVICE
DEVICE
DEVICE
DEVICE
DEVICE
DEVICE
APP
APP
36. Finding connections (pathfinding)
• How are these two parties connected?
37
Graph Algorithm Examples
Finding influencers (community detection)
• Will this individual’s friends churn?
Finding key components (centrality)
• What components do we depend upon?
What can’t fail?
39. Our Neo4j activity implementation has led to a great decrease in complexity, storage, and
infrastructure costs. Our full dataset size is now around 40 GB, down from 50 TB of data
that we had stored in Cassandra. We’re able to power our entire activity feed
infrastructure using a cluster of 3 Neo4j instances, down from 48 Cassandra instances of
pretty much equal specs. That has also led to reduced infrastructure costs. Most
importantly, it’s been a breeze for our operations staff to manage since the architecture is
simple and lean.”
David Fox, Adobe, Oct 2018
40
Customer Quote
How can Neo4j Services help you to get there?
40. Customer Use Case:
• Leading online platform to showcase and discover creative work
• More than 10 million members
• Allows creatives to share their work with millions of daily visitors
• Highlights Adobe software used in the creation process
• Drives people to the Adobe Creative Cloud
• Social platform for discovery, learning, and more
41
Adobe – Project Behance
Activity feed:
• Mongo DB (2011) - 125 nodes, dataset size of about 20tb
(terabytes)
• Cassandra (2015) - 48 nodes, dataset size of about 50tb
(terabytes)
• Neo4j (2018) - 3 nodes, dataset size of 33gb (gigabytes)
5 day
BOOTCAMP
41. 42
Large Chemical Producer and Supplier
Customer Journey
5 day Bootcamp
Educate Customer on Graph
technology
Demonstrate that BOM use cases are
a good fit for Neo4j
Build a small graph prototype
42. 43
Large Chemical Producer and Supplier
Customer Journey
5 day Bootcamp 30 day POC
Load subset of real life data (C4)
Build a GUI prototype to
demonstrate value to end-users.
Initial roll-out to power users
43. 44
Large Chemical Producer and Supplier
Customer Journey
5 day
BOOTCAMP
30 day POC FULL PROJECT OWNERSHIP (200md)
Data for multiple production chains
Improved GUI
Add profit margin calculation across
value chain
44. 45
Large Commercial Bank
Customer Journey
INNOVATION
LAB
STAFF AUGMENTATION
CAMPAIGN MGMT
INNOVATION
LAB
FRAUD PROJECT
80 mandays
TBD
YET ANOTHER
INNOVATION LAB
45. 46
Conclusion
• Neo4j PS makes customer projects successful
• through enablement
• through project / solution delivery
• Graph Based Solutions as accelerators
• Neo4j is the foundation for AI and ML
• Customer are using Neo4j for their success