The document discusses the future of data management through the use of an enterprise data hub (EDH). It notes that an EDH provides a centralized platform for ingesting, storing, exploring, processing, analyzing and serving diverse data from across an organization on a large scale in a cost effective manner. This approach overcomes limitations of traditional data silos and enables new analytic capabilities.

1. The
Future
of
Data
Management:
The
Enterprise
Data
Hub
Clarke
Pa)erson|
Sr.
Director,
Cloudera
1
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Inc.
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2. Data
PotenAal
is
Out
There
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2

3. An
Environment
of
Change
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3
ConsumpAon
InstrumentaAon
Value
ExploraAon

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4

5. 5

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8. ©2014
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8

9. IT’S
ALL
(BIG)
DATA
10TB
to
10PB
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Inc.
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rights
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9

10. 0%
10%
20%
30%
40%
50%
60%
Mainframe
Enterprise
Data
Warehouse
Storage
AnalyAc
Databases
ETL
Processing
What
Infrastructure
Have
you
Augmented
with
Big
Data
SoluAons?
Source:
King
Research,
3922
Respondents
©2014
Cloudera,
Inc.
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rights
reserved.
10

11. ©2014
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ComplicaAons
of
Status
Quo
Structure
Storage
Network
Silos
INGEST
STORE
EXPLORE
PROCESS
ANALYZE
SERVE
11

12. How
Important
are
These
CapabiliAes
in
Your
SelecAon
of
a
Big
Data
Vendor?
7
7.5
8
8.5
9
9.5
Open
Source
Socware
Technically
Superior
Product
Cost
IntegraAon
with
Other
Systems
Secure
Technology
Reliable
/
Trusted
Vendor
Flexibility
Performance
Scalability
Source:
King
Research,
3922
Respondents
©2014
Cloudera,
Inc.
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rights
reserved.
12

13. ©2014
Cloudera,
Inc.
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reserved.
13

14. What
are
the
Primary
Benefits
You’ve
Seen
Doing
a
Big
Data
Product
with
an
EDH
Source:
King
Research,
3922
Respondents
10%
30%
50%
70%
Gain
CompeAAve
Advantage
Improve
Efficiency
Increase
Business
Value
from
Data
Make
Be)er
Decisions,
Faster
Improved
Data
Processing
Improved
Data
AnalyAcs
©2014
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Inc.
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rights
reserved.
14

15. 15%
25%
35%
45%
OperaAonal
Improvement
Customer
Experience
Analysis
Market
TargeAng
Customer
Insights
Behavioral
Analysis
Research
/
InnovaAon
©2014
Cloudera,
Inc.
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rights
reserved.
What
are
Your
Big
Data
ApplicaAons?
15
Source:
King
Research,
3922
Respondents

16. ©2014
Cloudera,
Inc.
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rights
reserved.
Expanding
Data
Requires
A
New
Approach
16
Then
Bring
Data
to
Compute
Now
Bring
Compute
to
Data
Data
InformaFon-­‐centric
businesses
use
all
Data:
MulF-­‐structured,
Internal
&
external
data
of
all
types
Compute
Compute
Compute
Process-­‐centric
businesses
use:
• Structured
data
mainly
• Internal
data
only
• “Important”
data
only
Compute
Compute
Compute
Data
Data
Data
Data

17. Hadoop
Changes
the
Game:
Storage
and
Compute
on
One
Plalorm
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Inc.
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rights
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17
The
Hadoop
Way
The
Old
Way
$30,000+
per
TB
Expensive
&
UnaWainable
• Hard
to
scale
• Network
is
a
bo)leneck
• Only
handles
relaAonal
data
• Difficult
to
add
new
fields
&
data
types
Expensive,
Special
purpose,
“Reliable”
Servers
Expensive
Licensed
So[ware
Network
Data
Storage
(SAN,
NAS)
Compute
(RDBMS,
EDW)
$300-­‐$1,000
per
TB
Affordable
&
AWainable
• Scales
out
forever
• No
bo)lenecks
• Easy
to
ingest
any
data
• Agile
data
access
Commodity
“Unreliable”
Servers
Hybrid
Open
Source
So[ware
Compute
(CPU)
Memory
Storage
(Disk)
z
z

18. ©2014
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18
The
Old
Way
Expensive
&
UnaWainable
The
Hadoop
Way
Affordable
&
AWainable
Hadoop
Changes
the
Game:
Storage
and
Compute
on
One
Plalorm

19. ©2014
Cloudera,
Inc.
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rights
reserved.
The
Old
Way:
Bringing
Data
to
Compute
19
Complex
Architecture
• Many
special-­‐purpose
systems
• Moving
data
around
• No
complete
views
Missing
Data
• Leaving
data
behind
• Risk
and
compliance
• High
cost
of
storage
Time
to
Data
• Up-­‐front
modeling
• Transforms
slow
• Transforms
lose
data
Cost
of
AnalyFcs
• ExisAng
systems
strained
• No
agility
• “BI
backlog”
4
1
2
3
SERVERS
MARTS
EDWS
DOCUMENTS
STORAGE
SEARCH
ARCHIVE
ERP,
CRM,
RDBMS,
MACHINES
FILES,
IMAGES,
VIDEOS,
LOGS,
CLICKSTREAMS
EXTERNAL
DATA
SOURCES

20. ©2014
Cloudera,
Inc.
All
rights
reserved.
The
New
Way:
Bringing
Compute
to
Data
20
SERVERS
MARTS
EDWS
DOCUMENTS
STORAGE
SEARCH
ARCHIVE
ERP,
CRM,
RDBMS,
MACHINES
FILES,
IMAGES,
VIDEOS,
LOGS,
CLICKSTREAMS
ESTERNAL
DATA
SOURCES
Diverse
AnalyFc
Pla]orm
• Bring
applicaAons
to
data
• Combine
different
workloads
on
common
data
(i.e.
SQL
+
Search)
• True
analy*c
agility
4
1
2
3
4
AcFve
Compliance
Archive
• Full
fidelity
original
data
• Indefinite
Ame,
any
source
• Lowest
cost
storage
1
Persistent
Staging
• One
source
of
data
for
all
analyAcs
• Persist
state
of
transformed
data
• Significantly
faster
&
cheaper
2
Self-­‐Service
Exploratory
BI
• Simple
search
+
BI
tools
• “Schema
on
read”
agility
• Reduce
BI
user
backlog
requests
3

21. ©2014
Cloudera,
Inc.
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rights
reserved.
Hadoop
and
The
Enterprise
Data
Hub
21
Open
Source
Scalable
Flexible
Cost-­‐EffecFve
✔
Managed
✖
Open
Architecture
✖
Secure
and
Governed
✖
✔
✔
✔
3RD
PARTY
APPS
STORAGE
FOR
ANY
TYPE
OF
DATA
UNIFIED,
ELASTIC,
RESILIENT,
SECURE
CLOUDERA’S
ENTERPRISE
DATA
HUB
BATCH
PROCESSING
ANALYTIC
SQL
SEARCH
ENGINE
MACHINE
LEARNING
STREAM
PROCESSING
WORKLOAD
MANAGEMENT
FILESYSTEM
ONLINE
NOSQL
DATA
MANAGEMENT
SYSTEM
MANAGEMENT
,
SECURE

22. ©2014
Cloudera,
Inc.
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rights
reserved.
The
Power
of
the
EDH
22
THE
OLD
WAY
EDH

23. ©2014
Cloudera,
Inc.
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rights
reserved.
TransformaAve
ApplicaAons
Drive
Revenue
23
5%
15%
25%
35%
45%
Research
/
innovaAon
Behavioral
analysis
Customer
insights
MarkeAng
targeAng
/
Customer
experience
OperaAons
improvement
Fraud
prevenAon
and
Pricing
analyAcs
and
choice
Risk
Modeling
/
Network
monitoring
Service
quality
Customer
lifecycle
Capacity
forecasAng
Inventory
management
eDiscovery
/
document
What
are
your
Big
Data
ApplicaAons?
Source:
King
Research
survey,
September
2013,
3,922
Respondents

24. So
How
Do
We
Get
There?
24
©2014
Cloudera,
Inc.
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rights
reserved.

25. The
Typical
Enterprise
Data
AnalyAcs
Stack
Business
Intelligence
/
ApplicaFons
RDBMS
ETL
Processing
Staging
/
Storage
CollecFon

26. Step
1:
EDH
for
Storage/Staging/AcAve
Archive
Business
Intelligence
/
ApplicaFons
RDBMS
ETL
Processing
EDH
for
Storage
AcFve
Archive
CollecFon

27. EDH
for
CollecFon
&
Storage.
Step
2:
EDH
for
Data
CollecAon
(Sqoop/Flume)
Business
Intelligence
/
ApplicaFons
RDBMS
ETL
Processing

28. Step
3:
EDH
for
ETL
Processing
AcceleraAon
Business
Intelligence
/
ApplicaFons
RDBMS
EDH
for
CollecFon,
Storage
&
ETL
Processing
AcceleraFon.
ETL
/
Data
IntegraAon
Tools

29. Step
4:
EDH
for
EDW
OpAmizaAon
(Impala)
EDH
for
CollecFon,
Storage,
ETL
Processing
AcceleraFon
&
Historical
RDBMS
Data/Queries.
Business
Intelligence
/
ApplicaFons
RDBMS
Rarely
Used
Data

30. Step
5:
EDH
for
Agile
ExploraAon
EDH
for
CollecFon,
Storage,
ETL
Processing
AcceleraFon,
Historical
RDBMS
Data/Queries,
And
Agile
ExploraFon
RDBMS
BI
/
ApplicaFons
Agile
ExploraFon

31. Step
6:
EDH
for
Data
Science
(Not
Only
SQL)
EDH
for
CollecFon,
Storage,
ETL
Processing
AcceleraFon,
Historical
RDBMS
Data/Queries,
&
Generic
Data
ComputaFon
RDBMS
BI
/
ApplicaFons
Agile
ExploraFon
Data
Science

32. Step
7:
Converged
AnalyAcs
-­‐
Apps
Come
to
Data
EDH
for
CollecFon,
Storage,
ETL
Processing
AcceleraFon,
Historical
RDBMS
Data/Queries,
Generic
Data
ComputaFon,
And
MulFple-­‐Workloads.
RDBMS
BI
Explore
Data
Science
SAS,
R,
Spark
InformaFca
SyncSort,
Pentaho
Hunk
...

33. Data
Science
Agile
ExploraFon
ETL
AcceleraFon
OperaFonal
Efficiency
(Faster,
Bigger,
Cheaper)
TransformaFve
ApplicaFons
(New
Business
Value)
Cheap
Storage
Business
IT
A
High
Level
View
of
the
Journey
©2014
Cloudera,
Inc.
All
Rights
Reserved.
EDW
OpFmizaFon
Converged
AnalyFcs

34. WEB/MOBILE
APPLICATIONS
ONLINE
SERVING
SYSTEM
ENTERPRISE
DATA
WAREHOUSE
ENTERPRISE
REPORTING
BI
/
ANALYTICS
MACHINE
LEARNING
CONVERGED
APPLICATIONS
CLOUDERA
MANAGER
META
DATA
/
ETL
TOOLS
ENTERPRISE
DATA
HUB
©2014
Cloudera,
Inc.
All
Rights
Reserved.
The
Modern
InformaAon
Architecture
Data
Architects
System
Operators
Engineers
Data
ScienFsts
Analysts
Business
Users
Customers
&
End
Users
SYS
LOGS
WEB
LOGS
FILES
RDBMS

35. Enabling
The
App
Store
of
Big
Data
So[ware
(BI,
AnalyFcs,
&
Data
IntegraFon)
System
IntegraFon
Cloud
&
MSP
Hardware
Database
Note:
Display
Cloudera
Connect
PlaAnum
and
Gold
partners
only
©2014
Cloudera,
Inc.
All
rights
reserved.

36. Customer
Success
Across
Industries
Financial
&
Business
Services
Telecom
&
Technology
Healthcare
&
Life
Sciences
Media
&
InformaAon
Retail
&
Consumer
Energy
&
Public
Sector
©2014
Cloudera,
Inc.
All
rights
reserved.

37. Enterprise
Data
Hub:
A
Complete
Big
Data
SoluAon
• Efficient
Data
Management
System
• Consolidated
Silos
for
Truly
Big
Data
• Accelerated
Time
to
Insight
• Diverse
Business
User
CapabiliAes
• Full-­‐Fidelity
AcAve
Archive
• Enterprise-­‐Grade
Data
Security,
Lineage,
AudiAng,
Governance
• High
OpAon
Value
for
ExploraAon,
Data
Science,
Consolidated
360o
View
• Complete
Plalorm
for
Converged
AnalyAcs
©2014
Cloudera,
Inc.
All
rights
reserved.

38. Thank
You!
38
©2014
Cloudera,
Inc.
All
rights
reserved.