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C360	and	Graph
What	we	will	cover	
•  What	is	a	Customer	360	
•  Journey	to	C360	
•  What	is	graph?	
•  How	Graph	can	help	your	C360
Why	are	people	building	C360
Customer 360 (C360)
Gain a singular, contextual view of the
customer in real-time, for a seamless
customer experience across all
touchpoints.
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?
Finance	&	
Billing	
Customer	
Support 		
MarkeEng	
Website	
Mobile	
App	
Orders	
Inventory
Next	step	
Finance	&	
Billing 		
Customer	
Support 		 MarkeEng	
Website	
Mobile	
App	
Orders	
API	API	 API	
API	API	API	
ApplicaEon
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
Customer	
Call	log	
Product	 Product	
reviews	
Orders	
Inventory	
Offers	
Disconnected	tables	
	
Data	sEll	silo’d	
	
GeVng	from	
customer	to	
inventory	impossible
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
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
Vertex	
Customer	
Vertex	is	roughly	equal	to	an	enEty	in	a	tradiEonal	world	
	
Noun
Edge	
RelaEonship	
DirecEonal	
	
Verb
©	2016	DataStax,	All	Rights	Reserved.	 14
©	2016	DataStax,	All	Rights	Reserved.	 15
©	DataStax,	All	Rights	Reserved.	 16
©	2016	DataStax,	All	Rights	Reserved.	 17
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
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.
Comparing to SQL
DataStax	is	a	registered	trademark	of	
DataStax,	Inc.	and	its	subsidiaries	in	the	
United	States	and/or	other	countries.	
20
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
Where	do	we	see	GraphDBs	in	the	
wild?	
•  Social	networks	
•  logisEcs	
•  Manufacturing		
•  Health	care	
•  Fraud	DetecEon	
•  RecommendaEons	
•  Networking	
•  IdenEfy	&	access	managment	
•  C360
Customer	
Visits	website	
Read	reviews	
Order		
Sign	up	for	
Credit	card	
Delivery	
Delivery	
company	
Inventory	
InstallaEon	
Tech	support	
installer	
Returns	
product
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
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?
Pawern	matching	
What	path	through	the	buying	
journey	lead	to	the	most	
conversions?	
	
What	manufacturing	lines	lead	
to	the	most	defects?
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

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