The document discusses big data and analytics. It explains that big data refers to extremely large datasets that are difficult to manage with traditional tools due to their size. It also discusses how distributed computing helps address bottlenecks in analyzing big data by allowing inexpensive addition of multiple machines to a computing network. The document also provides an overview of how Splunk can help create a single customer view by ingesting and analyzing structured and unstructured data from various sources in real-time.

1. >
Small
vs.
Big
Data
<
What
the
heck?
What
does
it
all
mean
and
how
does
it
help
me?

2. >
Smart
data
driven
marke5ng
“Using
data
to
widen
the
funnel”
Media
A8ribu5on
&
Modeling
Op5mise
channel
mix,
predict
sales
Targe5ng
&
Merchandising
Increase
relevance,
reduce
churn
Tes5ng
&
Op5misa5on
Remove
barriers,
drive
sales
Boos5ng
ROI
June
2012
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Datalicious
Pty
Ltd
2

3. Twi8er
@datalicious
June
2012
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Datalicious
Pty
Ltd
3

4. >
Wikipedia:
Big
data
In
informaAon
technology,
big
data
consists
of
datasets
that
grow
so
large
that
they
become
awkward
to
work
with
using
on-­‐hand
database
management
tools.
DifficulAes
include
capture,
storage,
search,
sharing,
analyAcs,
and
visualizing.
This
trend
conAnues
because
of
the
benefits
of
working
with
larger
and
larger
datasets
allowing
analysts
to
spot
business
trends,
prevent
diseases,
combat
crime.
Though
a
moving
target,
current
limits
are
on
the
order
of
terabytes,
exabytes
and
zeMabytes
of
data.
June
2012
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Datalicious
Pty
Ltd
4

5. Big
data
=
bo8lenecks
June
2012
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Datalicious
Pty
Ltd
5

6. >
Big
data
analy5cs
bo8lenecks
Fast
laptops
now
have
up
to
8GB
of
RAM,
that
means
you
can
compute
up
to
6GB
of
raw
data
very
fast
in
memory
thus
bypassing
the
biggest
boMleneck:
I/O
June
2012
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Datalicious
Pty
Ltd
6

7. >
Power
vs.
distributed
compu5ng
Adding
more
supercomputers
is
difficult
as
they
are
complex
and
expensive
but
adding
machines
to
a
distributed
compuAng
network
is
fairly
cheap
and
‘easy’.
June
2012
©
Datalicious
Pty
Ltd
7

8. Big
data
=
hype?
June
2012
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Datalicious
Pty
Ltd
8

9. >
Importance
of
research
experience
The
consumer
decision
process
is
changing
from
linear
to
circular.
Considera5on
set
now
grows
during
(online)
(Online)
Research
research
phase
which
increases
importance
of
user
experience
during
that
phase
June
2012
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Datalicious
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9

10. >
The
consumer
data
journey
To
transac5onal
data
To
reten5on
messages
From
suspect
to
prospect
To
customer
Time
Time
From
behavioural
data
From
awareness
messages
June
2012
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Datalicious
Pty
Ltd
10

11. >
Single
customer
view
is
key
Website
behavioural
data
Campaign
response
data
+
The
whole
is
greater
than
the
sum
of
its
parts
Customer
profile
data
June
2012
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Datalicious
Pty
Ltd
11

12. >
Maximise
iden5fica5on
points
160%
140%
120%
100%
80%
60%
−−−
Probability
of
idenAficaAon
through
Cookies
40%
20%
0
4
8
12
16
20
24
28
32
36
40
44
48
Weeks
June
2012
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Datalicious
Pty
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12

13. >
Tradi5onal
single
customer
view
Website
Vendor
Reports
and
Repor5ng
data
data
feed
#1
dashboards
data
warehouse
Call
center
Vendor
Targeted
Transac5on
data
data
feed
#2
campaigns
data
warehouse
Customer
Vendor
Data
import
data
data
feed
#3
(ETL)
process
June
2012
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Datalicious
Pty
Ltd
13

14. >
Tradi5onal
single
customer
view
Challenge
#3:
Increasing
number
Website
Vendor
Reports
and
Repor5ng
of
(unstructured)
data
data
feed
#1
data
warehouse
dashboards
data
sources
Challenge
#1:
Rigid
database
Call
center
Vendor
Targeted
data
data
feed
#2
schema
requires
Transac5on
campaigns
data
warehouse
extensive
planning
and
maintenance
Challenge
#2:
Customer
Data
feeds
require
Vendor
Data
import
data
constant
u3
data
feed
# pdates
(ETL)
process
and
maintenance
June
2012
©
Datalicious
Pty
Ltd
14

15. >
Splunk
single
customer
view
SuperTag
Splunk
saved
Website
integra5on
for
searches
and
data
real-­‐5me
data
dashboards
Splunk
Splunk
regex
Call
center
Splunk
instance
Forwarder
for
builder
and
data
on
dedicated
data
import
data
exports
AWS
server
3rd
party
data
3rd
party
Customer
mining
and
campaign
data
repor5ng
execu5on
June
2012
©
Datalicious
Pty
Ltd
15

25. >
Key
Splunk
advantages
§ Powerful
data
mining
– Structured
and
unstructured
data
§ Easy
sharing
of
insights
– Online
dashboards
and
reports
§ Short
project
duraAon
– Quick
implementaAon
and
1st
insights
§ IntegraAon
with
other
plaeorms
– Regex
builder
and
data
extracts
§ Low
technology
and
resource
costs
– ImplementaAon
and
maintenance
June
2012
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Datalicious
Pty
Ltd
25

26. Contact
us
cbartens@datalicious.com
Learn
more
blog.datalicious.com
Follow
us
twi8er.com/datalicious
June
2012
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Datalicious
Pty
Ltd
26

27. Data
>
Insights
>
Ac5on