7. 7
Car
name: “Dan”
born: May 29, 1970
twitter: “@dan”
name: “Ann”
born: Dec 5, 1975
since:
Jan 10, 2011
brand: “Volvo”
model: “V70”
Anatomy of a Property Graph Database
Nodes
• Represent the objects in the
graph
• Can be labeled
Relationships
• Relate nodes by type and
direction
Properties
• Name-value pairs that can go
on nodes and relationships.
LOVES
LOVES
LIVES WITH
Person Person
9. 9
Some Examples of Typical Automotive Data
Event DataProduct
Data
Customer DataOrganizational
Data
3rd Party Data
Documentation
Facilities
Processes
Systems and
Databases
KPIs and Reports
Personal Data
Customer
Relationships
Documentation
Processes
Product Details
Product
Hierarchy
Bills of Materials
Sensor /
Telematics Data
Warranty Claims
Customer Contact
Social Media
Market Data
Organisational
Hierarchy
Corporate Data
Supply Chain Data
Supplier Data
Logistics Data
Inventory Data
Dealer Data
11. Supply Chain Example
Graph
Organisational Data
Customer Data
Product Data
Event Data
3rd Party Data
Created using https://neo4j-arrows.appspot.com/
Supply Chain Data
11
12. 12
Supply Chain Graph Uses
• Can I use the graph to help me improve my ordering
and procurement processes?
• Can the graph help me save money on orders?
• Can I optimize my inventory using a graph?
• Can the graph help me with comparative analysis of
my suppliers and their products?
Yes!
Yes!
Yes!
Yes!
13. Organisational Data
Customer Data
Product Data
Event Data
3rd Party Data
Warranty Analytics Example
Graph
13
Supply Chain Data
Created using https://neo4j-arrows.appspot.com/
14. 14
Warranty Analytics Graph Uses
• Can I find patterns in the graph indicating
inappropriate claims or warranty fraud?
• Can I use the graph to help predict future claims?
• Can the graph help me manage my warranty and recall
risk?
• Can I use the graph to help me understand whether
faults might be caused by supplier issues?
Yes!
Yes!
Yes!
Yes!
15. 15
Customer 360 View Example Gr
Organisational Data
Customer Data
Product Data
Event Data
3rd Party Data
Created using https://neo4j-arrows.appspot.com/
Supply Chain Data
16. 16
Customer 360 View Graph Uses
• Can I use the customer 360 view graph to improve my
customers’ experience?
• Can I use the customer 360 view graph to identify high
Lifetime Value customers?
• Can I use the customer 360 view graph to detect and
prevent churn?
• Can I use the customer 360 view graph to improve
upsell and cross-sell?
Yes!
Yes!
Yes!
Yes!
18. 18
Knowledge Graph Uses
• Can I use a knowledge graph to improve my products
and services?
• Can a knowledge graph help improve my product time-
to-market?
• Can I use a knowledge graph for customer-facing use
as well?
Yes!
Yes!
Yes!
19. 19
Other Automotive and Manufacturing Graph Use
Cases
• Identity and Access Management
• Infrastructure and Network Management
• Master/Meta-data Management
• Regulatory Compliance (i.e. GDPR)
This slide builds from left to right with animations.
Organisational Data : data you hold within your company, and is generally only accessible within your company (or in limited ways externally). This includes your corporate documentation, data about your processes, data about your employees and organizational hierarchy, KPIs and reports, and your IT infrastructure (systems and databases). This information is often very siloed.Customer Data : this is all the data you have on your customers, whether they are corporate or individual customers. This includes their address, personal data, and documents related to them (i.e. contracts). You may also have information about relationships between your customers (either between individuals, or between individuals and companies). This may live in different systems, or be centralized in your CRM system.
Products and Services Data : information about all of your products including any documentation and processes specific to these products, the details about different products, a product hierarchy (i.e. brand, vehicle line, different options available), and bills of materials related to your products. There could be different types of bills of materials – for example Manufacturing BOM, Engineering BOM, Configurable BOM, etc. You may also want to store different snapshots of a BOM … the generic design, the BOM for a product as built, and iterations of that as it’s been repaired/upgraded over time.
Event Data : this is data about specific events. This could include sensor or telematics data, individual claims, and customer contacts (i.e. call centre).
3rd Party Data : data you bring in from outside, like social media data, market data, press releases, news stories, studies and surveys, etc. Data about and from your dealer network is also included here (Customer data from your dealers might also be classified here, if you want to be specific).This is not an exhaustive list of data categories, it’s more indicative of the types of data a manufacturer / automotive company could be working with.
The Knowledge Graph example graph is very ‘green’ as it’s mostly about improving access to data for customers (this is a retail customer example). An internal knowledge graph would probably be more red, or a mix of red and green.
This slide illustrates the types of data you might look at to build your knowledge graph.
This customer has several products already, so the knowledge they might be seeking could need to be quite specific to the products they have.
If they are looking for information about products they don’t have, then going to the general documentation is probably appropriate.
Three is also information about the teams who manage specific products, in case they need to reach a real person.
This knowledge graph could be used to improve search engine capability/results, as well as power a self-service support chatbot.
Can I use knowledge graph to improve customer experience? Yes – you can use a Knowledge graph to help drive effective self-service support, for example, using a search engine.
Can I use the knowledge graph with chatbots as well as search engines? Yes – the eBay shopbot example is a good one for this. Chatbots powered by a knowledge graph can be more effective.
Can I use a knowledge graph internally as well? Yes – this example was for an external-facing knowledge graph, but an internal one (again, using a search engine or a chatbot) could help your employees as much as an externally-facing one could help customers!
These are more industry-agnostic but still applicable to Manufacturing / Automotive.
The real power of Neo4j isn’t in working with small graphs like the examples we’ve seen. It’s when your data looks like this! Being able to work with data and spot patterns at scale in real time is critical to these Banking use cases, and only Neo4j can bring that power to your business.