6. Goals
“Know” our customers
through consistent engagement
Improve customer experiences
and outcomes
Effectively identify and
mitigate risks
Identify opportunities for
additional value
6
Understand innovative
power of graph
Correctly and efficiently
apply graphs to business problem
Implement/adapt fast
and manage risks
Leverage software investment
1
2
3
4
12. 12
Innovation Lab
Help you accelerate innovation through
graph thinking
How we do it
Generate and prototype graph projects
together with customers and prospects
Format
3.5 day workshop, 2-3 Neo4j participants
Outcome
Provide a deep understanding of graph
thinking and the innovation opportunities of
adapting graph technology
13. 13
Graph modeling session
Verify use case feasibility
How we do it
Interactive requirements whiteboarding and
brainstorm session
Format
0.5 day workshop, 1 expert modeler
Outcome
Validated graph modeling and graph access
scenarios. Understanding of use case
complexity
14. 15
Reference project
Talk with expert(s) through implementation
of a similar use case
How we do it
Discussion and presentation
Format
1-2hr phone call
Outcome
Understand high level project set-up: T-shirt
sizing of your project, identifying typical
hurdles, identify skills/team needed,
architectural components.
17. 21
Why a Native Graph Database for MDM?
● Connect data from heterogeneous sources
○ connect data in movement
○ connect data at rest
● Agility
○ connect additional sources as needed
○ without strict schema 360 degree view is possible
○ without strict schema, alternatives can be modelled
● Lineage and traceability
○ tracking how/when/what data was loaded = graph
○ which can be stored with the data
● Intuitiveness
○ connected data can be shared in the entire organisation
● Speed:
○ access to MDM data with high performance 24x7 enabled
19. 2323
Bootcamp
Accelerate graph learning to allow
Customers to evaluate graph technology
How we do it
Hands on training and prototyping
Format
5 day training/workshop and Q&A
Outcome
Technical team has overall understanding of
technical capabilities of Neo4j based on hands
on experience with the toolset.
20. 2424
Proof of concept
Build a small, working solution, proving out a
select set of business requisites
How we do it
Clear scope, design and build
Format
Project
Outcome
Working solution (limited features)
Demo/presentation
Backlog and roadmap for further extensions
21. 2525
Solution Design Workshop
Requirements analysis and solution design
exercise for full graph solution
How we do it
Requirements collection, analysis, create
product backlog and solution architecture
Format
Workshop (typically 5 days but depends … )
Outcome
Product backlog
Solution architecture/design document
Suggested project plan / road map
22. 26
How we can contribute to project definition
Validated choice of Neo4j as the tool to solve your “graph problem”
BUT ALSO:
• Awareness of data integration/quality challenges
• Wider application design:
• UI/UX and APIs
• Security aspects
• Operations and admin aspects
• CI/CD
• Project definition: known hurdles, risks, …
26. 3030
Solution Audit &
Upgrades
Revisit requirements, ensure alignment with
product roadmap, leverage new features
How we do it
Audit Workshop & training
Outcome
Recommendations for
1) improved solution
2) Upgrade
3) New features
27. ● Strike a balance between schema-less and enforcing constraints
● Use graph to model “uncertainty” and alternatives
● Consider data integration with data in movement or data at rest
● Picking right data integration tools
● Handling master data update priorities and business logic
● How to convince end-users the new data store is correct
31
Where we make a difference on MDM implementation
29. Add structure to unstructured data
Use taxonomies and ontologies
Relate the data/content to model
Use free text search
Ability to easily navigate
unstructured data
33
Knowledge graphs
Pdf Files E-Mails
TECHNICAL
DATA
Relational
DBs
3rd party
Open SourceCRM
OCR / NLP
30. 36
Types of knowledge graphs
Internal knowledge
documents & files, with
meta data tagging
External data source
aggregation mapped to
entities of interest
Context Rich Search External Event Insight
Sensing
Enterprise NLP
Graph technical terms,
acronyms, abbreviations,
misspellings, etc.
Examples:
• MDM, Search
• Customer support
• Document classification
Examples:
• Supply chain/compliance risk
• Market activity aggregation
• Sales opportunities
Examples:
• Improved search
• Chatbot implementation
• Improved classification
Context Independent
Warehouse
Real-Time WarehouseLogical Warehouse
31. 37
Where we make a difference with Knowledge Graphs
• Understand how to deal with semi-structured and unstructured data
• Design a data load strategy
• Working with taxonomies, ontology, context, multi-language
• Identify tools and partners to assist with the non-Neo4j parts of the
project
33. 40
Network Management
Unified Network Inventory -> Network Reconciliation
Service Orchestration -> Automation
Service Assurance -> Fault Management
Planning -> Traffic Intelligence
Performance and Quality Management and
Analytics
34. Network Management projects with Neo4j
41
● Steps and decisions to be taken:
○ Identify reusable modules
■ Connectors to standard sources (Inventory Systems, Network Discovery Tools,
Element Managers)
■ Path Computation Algos (Dijkstra, Steiner…)
■ Impact Analysis / Root Cause Analysis
■ UI: Map Based Circuit View
○ Neo4j Field Engineering guides and helps you through the configuration and utilisation of
the modules
○ Building integrations with your architecture elements as needed
■ Producers : Inventory Systems, Network Managers, Network Discovery Tools
■ Consumers : Event Aggregation Platforms, BI tools, Orchestration Platforms
35. Leverage the knowledge and expertise of
our field team who helped world leaders
build their graph solutions...
42
38. 45
Solutions
What?
Innovative, market-leading, Neo4j-based Business Solutions for our Enterprise
Customers and Partners
Why?
• Reduce Risk and TCO
• Rapid business value via our PS or approved solution partners
• Enables customer use cases in record timeframes
• Speeds up POC development, enables solution visualization for internal selling
• Built on extensible and customizable, solution-tuned frameworks
39. 46
Neo4j Solution Frameworks: for accelerated adoption & PoCs
Risk Management (for FS)Intelligent Recommendations Network Management
Human Capital ManagementPrivacy Shield (GDPR, CCPA, …)Fraud Analysis Framework
41. 4848
Cloud Managed Service
We manage your Neo4j database
How we do it
Standardized set-up and configuration
Dedicated 24/7 Neo4j monitoring
Dedicated CMS support team
Backup/restore on request
Outcome
Fully hosted database service
43. ● Our team of trained field engineers combined with the customer’s
SMEs successfully deploy:
○ Exploratory Data Analysis
○ Apply Neo4j’s Graph Algorithms
○ APOC + Labs + Custom Libraries
○ Python Notebooks
50
Graphs and Data Science
44. Neo4j’s field team has helped customer
Data Science teams applying Graph
Algorithms to...
Pathfinding
& Search
Centrality /
Importance
Community
Detection
Complex diverse path
computation for Service
orchestration platform with major
UK telco provider.
Detecting payment fraud for
an international electric
utility company
Entity resolution for Global
provider of animal care
services
Clinical trial similarity for
multinational
pharmaceutical company
Similarity
46. ● Neo4j database and platform is the foundation of a successful project / implementation for:
○ Master Data Management projects
○ Knowledge graphs
○ Network management
○ …. and multiple other use cases and industries
● Neo4j Field Engineering / Services assists and enables you for successful project
implementations throughout the full cycle of
○ Graph evaluation
○ Project definition
○ Implementation
○ Hosting
… and beyond
53
Conclusions