Big data solutions explained for marketeers & business executives

Explanation for marketeers
and business executives

Fried
Broekhof
November
2013
1
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Real time Adaptive Marketing

Big data’s V’s
Volume

Sta-c
Data
Exabytes
of

exis-ng
data
to

process

Velocity

Dynamic
Data
Streaming
data,

(near)
RT
response

Variety

Diﬀerent
Data
(Un-‐)structured
data,

text,
images,
video’s

VeracAty

Right
Data
Integrity
of
data.
Can

the
results
be
trusted?

Value

Valuable
Data
Business
value
of

exploring
data

VolaAlity:
How
long
do
you
need
to
store
this
data?
Validity:
Is
the
data
correct
and
accurate
for
the
intended
usage?

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Basic Principles

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It all started with ...

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It all started with ...

...a single server

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and an explosion of
data to be processed

...a single server

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We needed...

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...more computing power
and more storage

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... a distributed file system,
to share storage
and computing power
among servers

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and...

... a framework for writing applications
that processes large amounts of
structured and unstructed data in
paralel., in a reliable and fult-tolreant
manner.

Core
Hadoop
1.0

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but... we needed more...

efficient transfer of bulk data between
Apache Hadoop and structured datastores,
such as relational databases.

Data
Services

Core
Hadoop
1.0

RAM


but... we needed more...

a distributed real-time computation system
for processing fast, large streams of data

Data
Services

Core
Hadoop
1.0

RAM


...and...
a non-relational (NoSQL) database that runs on
top of the Hadoop® HDFS, that provides faulttolerant storage and quick access to large
quantities of sparse data. And allows users to
conduct updates, inserts and deletes.

Data
Services

Core
Hadoop
1.0

RAM


...and...

a library of scalable machine-learning
algorithms, implemented on top of Apache Hadoop®
and using the MapReduce paradigm.

Data
Services

Core
Hadoop
1.0

RAM


...but also...

a data warehouse infrastructure built on top of
Apache™ Hadoop® for providing data summarization,
ad-hoc query, and analysis of large datasets.

Data
Services

Core
Hadoop
1.0

RAM


...and...

a simple scripting language that allows users to
write complex MapReduce transformations.

Data
Services
Pig

Core
Hadoop
1.0

RAM


And a framework and tools...
...to manage it all...

OperaAonal
Services
Ambari

Falcon

Knox
Zookeeper

Oozie

Data
Services
Flume
Accumulo HCatalog

Core
Hadoop
1.0

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Hadoop evolved to

enable a broader array of interaction patterns
for data stored in HDFS beyond MapReduce
meet demands for fast response times and
extreme throughput at petabyte scale
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1 solution doesn’t fit all

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There is a lot to choose from

Non-Relational

Relational

Analytic
Dremel
Drill
ParAccel

Operational
Intersystems
Progress
Objectivity
Versant

Teradata
Aster

IBM InfoSphere HP Vertica
Netezza
Oracle
EMC
SAP Hana
Times-Ten
Greenplum SAP Sybase IQ

Hadoop
Horton
Cloudera
MapR
Hadapt
Zettaset
Spark

Oracle

Document MarkLogic
Lotus Notes

McObject

Couchbase
MongoDB
RavenDB
DaaS
MarkLogic
Key
Cloudant
Elasticsearch
Value
App Engine
Couchbase
SimpleDB
Riak
Redis
Big tables
Graph
Membrain
FlockDB
Voldemort
Big table
InfiniteGraph
BerkeleyDB
Hypertable
Neo4j
Dynamo
HBase
AllegroGraph
Cache
Accumulo
Cassandra
Giraph

NoSQL

IBM DB2

Infobright
ParAcell
Calpont
Vectorwise

SQLSVR JustOneDB

MySQL
Sybase ASE

Ingress

ProgreSQL

EnterpriseDB

NewSQL
HandlerSocket
Akiban
MySQL Cluster
Clustrix
Drizzle
GenieDB
SchoonerSQL ScaleBase
ScalArc
Tokutek
CodeFutures NimbusDB
Continuent
VoltDB
Translattice
Spanner
Amazon RDS
SQL Azure
Database.com
Xeround
FanthomDB

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How about BI vendors?

21
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BI
vs
Big
data
analyAcs
BI

Big
data
analy,cs

Structured
&
repeatable

IteraAve
&
exploraty
analysis

Business
users
determine
what
to
ask,
in

advance

IT
delivers
a
plaPorm
to
enable
creaAve

discovery

IT
structures
data
to
answer
quesAons

Business
explore
what
use
cases
should
be

conﬁrmed

Monthly
reports,
proﬁtabilty
analysis,

customer
surveys

brand
senAment,
product
strategy,

maximum
uAlizaAon,
segmentaAon

Control

vs

Explore
22
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What can you do with it?

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What
opportuni-es
do
we
spot?

25
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What hurdles?

26
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Marketing Analytics process

Maturity of Marketing Analytics within organizations

Real-time adaptability

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BD/Marke-ng
analy-cs
is
driving
business
transforma-on

29
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Who’s involved?

Data

Platform

Insights

Transformation

Data consultants

IT

Marketing/Business

Business consultants

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Capturing value....

Big data

Predictive and
optimization models
Organizational
transformation

...is an Iterative process
Collaborate
Step by Step
Test & learn

RAM


Do’s
•
•
•
•
•
•

Deﬁne
use
cases
Ask
the
right
quesAons
Be
creaAve
with
what
you
have
OpAmize
spend
and
impact
across
channels
Keep
reports
&
dashboards
simple
Work
incremental

32
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Cases
• ROI/impact
of
markeAng
campaigns
for
FMCG
– Improved
content
markeAng
– Improved
engagement
(11%)
– Cost
reducAon
of
markeAng
spend
(8%)

• RT
analyAcs
for
RT
bidding
engine
• SegmentaAon/deﬁning
promising
b-‐b

segments
for
a
lease
company
• Opportunity
spobng
for
health
insurance

33
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Big
Data
Lab
• 5
working
days
• Deliverable;
validated
use
case(s)
for
new
business

opportunity/opportuni-es

•
•
•
•

Steps
Explore
data
Deﬁne
uses
cases
Validate
uses
cases
Deﬁne
steps
based
on
outcome
valida-on
of

use
cases
34
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Big data in real life

Channel specific
Time-dependent
Personal
based on:
behavior
preferences
conversations
Centralized data
Reward
behavior
sharing
loyalty
participation
co-creation
feed-back

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Big data solutions explained for marketeers & business executives

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