1

Hadoop and the Future of Data ManagementMark J. LewisSenior Director MarketingEurope, Middle East & Africa

Twitter: @markjlewis

2

How do seed selection, planting density, ground slope, temperature, soil composition & weather interact to impact yields?

How much corn did my farm produce last year?

2

3

Can we just keep all our data on-line?

How do we set set policies about what data is worth keeping?

3

4

Can we avoid that cost altogether?

What’s our annual budget for enterprise data warehouse expansion?

4

55

How many cars are there in each parking lot?Can we use that information to refine our prediction?

How will seasonality affect our store’s earnings next quarter?

66

Which one of these people is likely to be carrying a bomb?

Do you have any liquids in your carry-on?

77

Which new technologies actually improve patient health?

What’s our budget for new equipment?

88

Is it possible to set rates based on actual risk for each particular house?

How big is your house? What are comparable insurance claims rates?

99

Information Driven

All of these organizationsare

1010

Information Driven

All of these organizationsneeded to change to become

11 ©2014 Cloudera, Inc. All rights reserved.11

Expanding Data Requires A New Approach

1980sBring Data to Compute

NowBring Compute to Data

Relative size & complexity

DataInformation-centric

businesses use all data:

Multi-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

12 ©2014 Cloudera, Inc. All rights reserved.12

The Old Way: Bringing Data to Compute

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 Analytics• Existing systems strained• No agility• “BI backlog”

4

1

2

3

SERVERSMARTSEDWS DOCUMENTS STORAGE SEARCH ARCHIVE

ERP, CRM, RDBMS, MACHINES FILES, IMAGES, VIDEOS, LOGS, CLICKSTREAMS EXTERNAL DATA SOURCES

13 ©2014 Cloudera, Inc. All rights reserved.13

From Hadoop to an Enterprise Data Hub

Open SourceScalableFlexibleCost-Effective

✔

Managed ✖Open Architecture ✖Secure and Governed ✖

✔

✔

✔

3RD PARTYAPPS

STORAGE FOR ANY TYPE OF DATAUNIFIED, ELASTIC, RESILIENT, SECURE

CLOUDERA’S ENTERPRISE DATA HUB

BATCHPROCESSING

MAPREDUCE

ANALYTICSQL

IMPALA

SEARCHENGINE

SOLR

MACHINELEARNING

SPARK

STREAMPROCESSINGSPARK STREAMING

WORKLOAD MANAGEMENT YARN

FILESYSTEMHDFS

ONLINE NOSQLHBASE

DATAM

ANAG

EMEN

TCLO

UD

ERA NAVIG

ATOR

SYSTEMM

ANAG

EMEN

TCLO

UD

ERA MAN

AGER

SENTRY, SECURE

1414

15 ©2014 Cloudera, Inc. All rights reserved.15

SERVERS MARTS EDWS DOCUMENTS STORAGE SEARCH ARCHIVE

ERP, CRM, RDBMS, MACHINES FILES, IMAGES, VIDEOS, LOGS, CLICKSTREAMS ESTERNAL DATA SOURCES

Diverse Analytic Platform• Bring applications to data• Combine different workloads on

common data (i.e. SQL + Search)• True analytic agility

4

1

2

3 4

The New Way: Bringing Compute to Data

Active Compliance Archive• Full fidelity original data• Indefinite time, any source• Lowest cost storage

1

Persistent Staging• One source of data for all analytics• 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

16

Data ScienceExplorationETLAcceleration

Operational Efficiency Information Advantage

CheapStorage

Business IT

Your Journey to Achieve Full Potential

©2014 Cloudera, Inc. All Rights Reserved.

EDWOptimization

Consolidation 360° View

Advance from Strategy to ROI with Best Practices and Peak Performance

17 ©2014 Cloudera, Inc. All rights reserved.

80% of Those Surveyed Are Planning, or Have Already Begun Big Data Projects

ETL process (Extract Transform Load)

Analytic databases

Storage

EDW (Enterprise Data Warehouse)

Mainframes

0% 10% 20% 30% 40% 50% 60%

Are Augmenting or ReplacedExisting Infrastructure (46% of all Respondents):

Source: King Research survey, September 2013, 3,922 Respondents

Key Insight: Multiple Overlapping Use Cases Require Converged Analytics

18

Thank you!Mark LewisTwitter @markjlewis

18