1.
C360 and Graph

2.
What we will cover
• What is a Customer 360
• Journey to C360
• What is graph?
• How Graph can help your C360

3.
Why are people building C360

4.
Customer 360 (C360)
Gain a singular, contextual view of the
customer in real-time, for a seamless
customer experience across all
touchpoints.

5.
Challenges
• How can I ensure our full customer profile is
current and comprehensive?
• How can I provide easy access to the current and
comprehensive customer profiles to many
different consumers?
• access to the Customer 360 is always available?
• How do I expose the relaEonships within our
Customer and Departmental Profiles for flexible
exploraEon?

6.
Finance &
Billing
Customer
Support
MarkeEng
Website
Mobile
App
Orders
Inventory

7.
Next step
Finance &
Billing
Customer
Support MarkeEng
Website
Mobile
App
Orders
API API API
API API API
ApplicaEon

8.
Stream processing
Finance &
billing
Customer
Support
MarkeEng Website Orders
Customer 360
API
WebSite Mobile App ReporEng
Data Hub – ESB – Message queue
Mobile
App
Website Inventory MarkeEng
Finance &
Billing
Customer
Support

9.
Customer
Call log
Product Product
reviews
Orders
Inventory
Offers
Disconnected tables
Data sEll silo’d
GeVng from
customer to
inventory impossible

10.
What is a Graph?
COUNTRY
ADDRESS
CUSTOMER
Rated
ORDER
PRODUCT
Line ItemShipping Address
Billing Address
Address
TAG
Resides
Purchased
Purchased
Has
Belongs To
Ships To
COUNTRY
ADDRESS
CUSTOMER
Rated
ORDER
PRODUCT
LineItem
ShippingAddress
BillingAddress
Address
TAG

11.
What is a graph made of?
COUNTRY
ADDRESS
CUSTOMER
Rated
ORDER
PRODUCT
Line ItemShipping Address
Billing Address
Address
TAG
Resides
Purchased
Purchased
Has
Belongs To
Ships To
COUNTRY
ADDRESS
CUSTOMER
Rated
ORDER
PRODUCT
LineItem
ShippingAddress
BillingAddress
Address
TAG
Vertex
Egde
Property

12.
Vertex
Customer
Vertex is roughly equal to an enEty in a tradiEonal world
Noun

13.
Edge
RelaEonship
DirecEonal
Verb

14.
© 2016 DataStax, All Rights Reserved. 14

15.
© 2016 DataStax, All Rights Reserved. 15

16.
© DataStax, All Rights Reserved. 16

17.
© 2016 DataStax, All Rights Reserved. 17

18.
ProperEes
Customer
Name: Connor
Age: 6
Grade: 1st
Product
Name: LunchBox
Color: Green
Logo: StarWars
Age: 5-15
Product
Name: T-shirt
Color: Red
Logo: Starwars
Age: 5-15
Added to list

19.
How is that different then a RDBMS?
RDBMS Graph
• EnEEes based
• Shallow 1:1 foreign key
relaEonships
• RelaEonship following down
mainly by JOINS and UNIONS
at query Eme
• Rigid data structure
• Table based
• SQL Query language
• All about the relaEonships.
• Deep, complex relaEonship
structure
• EnEEes are almost a second
class ciEzen.
• Flexible data structure
• No tables!
• Specialized Graph query
language.

20.
Comparing to SQL
DataStax is a registered trademark of
DataStax, Inc. and its subsidiaries in the
United States and/or other countries.
20

21.
DSE Graph – Data Access | Traversals
• Query Access => Apache TinkerPop Gremlin
• Traversal style data navigaEon
Find all orders purchased by Lisa • g.V().has('customer', 'name', 'Lisa').out('ordered').values('number')
• Find all products purchased by
Lisa’s Friends • g.V().has('customer', 'name',
'Lisa').outE('related').has('Type','friend').inV().out('ordered').out('purchased').val
ues('name’)
• RecommendaEon - find all
products purchased by Lisa’s
Friends, not purchased by Lisa
• g.V().has('customer', 'name',
'Lisa').as('customer').out('ordered').out('purchased').aggregate('produc
ts').in('purchased').in('ordered').where(neq('customer')).out('ordered').
out('purchased').where(without('products')).values('name')
© 2016 DataStax, All Rights Reserved. 22
1
Customer
Name:[Lisa]
Age:[32]
2
Order
Number:[1234]
5
Product
Name:[Socks]
Size: [XL]
4
Customer
Name:[Frank]
Age:[28]
6
Product
Name:[Shirt]
Size: [XL] 7
Address
Stree:[123 West Street]
Zip Code:[44534]
11
12 13
14
15
16
17
3
Tag
Type:[Color]
Value: [White]
18
19
orders
Date:[1/1/2016]
related
Type:Friend
resides
Since:1/1/2000
ships
Shipment Date:1/2/2016
purchased
Qty: 42
purchased
Qty: 1
has
Valid: 1/1/2012
has
Valid: 1/1/2012

22.
Where do we see GraphDBs in the
wild?
• Social networks
• logisEcs
• Manufacturing
• Health care
• Fraud DetecEon
• RecommendaEons
• Networking
• IdenEfy & access managment
• C360

23.
Customer
Visits website
Read reviews
Order
Sign up for
Credit card
Delivery
Delivery
company
Inventory
InstallaEon
Tech support
installer
Returns
product

24.
Example of C360 – A day in a life of a bank customer
2
6
paid her lunch using ABC
bank’s debit card
11am 9am
made purchase at local
flower shop with bank’s
credit card
3pm
paid credit card bills with her ABC
online banking checking acct
4:15p
m
6pm
Customer of Bank ABC with mulEple accounts and cards
Profile: 68 yrs old, female, Florida resident, no young family members, customer since 1995
A transacEon was
made using the
customer’s credit card
showing purchase of
motorcycle in Aruba
customer paid her grocery at
Safeway with check from the
ABC bank
real Eme alert was triggered due to unusual item and
locaEon purchase. Bank’s Fraud Department sent a text
msg to the customer to verify the purchase, and freezed
the card
customer got text msg from the bank, called customer service
rep in her local branch. The rep was already aware of the issue
and verified the motorcycle purchase was a fraud. The bank
invalidated customer’s credit card and issued a new card.
4:18p
m

25.
Betweenness, Wondering, Social influence.
How are two people
connected?
What reviews are most
influenEal?
What path through the
buying journey lead to
the most conversions?

26.
Pawern matching
What path through the buying
journey lead to the most
conversions?
What manufacturing lines lead
to the most defects?

27.
RecommendaEon
Connor Product
Type: T-shirt
Color: Red
Logo: StarWars
Age: 5-15
Purchased
Franchise Product Name: StarWars
Age Range
Type: LunchBox
Color: Red
Logo: Jar Jar
Age: 5-15