developing a successful big data business strategy

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DEVELOPING A SUCCESSFUL BIG DATA BUSINESS STRATEGY

SEBASTIAN DARRINGTONCTO - BIG DATA AND ANALYTICS, EMEA@THESTORAGECHAP


ALL ORGANISATIONS ARE ON A JOURNEY TO…

1000XMORE DATA

REAL TIMEOPERATION

ANALYTICINSIGHTS

PERSONALISATION & ENHANCED SERVICES


BIG DATA BUSINESS MODEL MATURITY INDEX

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Measures degree to which organisations have

integrated data and analytics into their business models

Key Business Processes

EconomicDrivers

BUSINESS OPTIMISATION

(PROCESS REFINEMENT)

PrescriptiveRecommendations

BUSINESS INSIGHTS

(PREDICITIVE)BUSINESS

MONITORING(REARWARD)

BUSINESSMETAMORPHOSIS(DATA AT HEART)

DATAMONETISATION(DATA DRIVEN PRODUCTS OR

SERVICES)


Capitalizing on new data sources to solve a

business problem that was not possible to solve with

conventional data management techniques

BUSINESSProblem we are trying to solve?

Build a Big Data Platform to meet immediate and long term needs to reduce the friction of provisioning data for innovation.The Data Lake

TECHNICALWhat data do we have available to us?

TWO PARTS OF THE JOURNEY


INGESTCapture data froma wide range of

sources, traditional and new

STOREStore everything in

one environment for cross data analysis

ANALYZEUse advanced

algorithms to discover new, predictive

patterns

SURFACEShare insights with business domain experts

ACTBuild data-driven

applications to meet business needs

JOURNEY TO DIGITAL BREAKS TRADITIONAL IT INFRASTRUCTURE

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ANALYTICS DATA

AGILE APPS

TRANSFORMATION

CREATING NEW DIGITAL CONSUMER EXPERIENCESIS NOT JUST ABOUT HOW YOU DEPLOY HADOOP OR USE DATA SCIENTISTS

PAST FUTURE

BUY PREPACKAGED APPLICATIONS

BUILD INFRASTRUCTURE

BUYPREPACKAGED

INFRASTRUCTURE BUILD

APPLICATIONS


BIG DATA TECHNOLOGY ADOPTION CURVE

INNOVATORS EARLY ADOPTERS LATE ADOPTERS

3+YEAR HADOOP VETRANS

CHALLENGE:INFRASTRUCTURE

Scalability Flexibility/Agility Enterprise Grade

STRUGGLING WITH WHAT NEXT

CHALLENGE:POINT SOLUTIONS

IngestionGovernance

Cloud Like M&A

UNSURE WHERE TO BEGIN

CHALLENGE:FAST TRACKArt of the PossiblePeople and Process

Buy vs. Build


THERE ARE MULTIPLE WAYS TO APPROACH

BUILD IT YOUSELF

BUILD IT WITH HELP

BUY VS BUILD


BUILD IT YOURSELF


BUILD IT WITH HELP


BUY VS. BUILD


THE BIG DATA, ANALYTICS & APPS JOURNEYSTART

DISPARATE DATA SILOS

STEP 1:

CONSOLIDATE AND TIER DATA

STEP 2:

ADD VIRTUALISEDHADOOP COMPUTE

STEP 3:

IMPLEMENT ANALYTICS

STEP 4:

INTEGRATEAPP DEV

STEP 5:

BUSINESS DATA LAKE

DATA LAKEFOUNDATION HADOOP ANALYTICS TOOLS PAASTECHNOLOGY

APPSANALYTICS

SELF SERVICEGOVERNANCE

DATA CURATION

INTEGRATE ALL DATA

LINK DATA SETS AND DATA ELEMENTS

COLLABORATE INTERNALLY &

EXTERNALLY

DRIVE NEW INSIGHTS, REFINE

PROCESSES

IT ENABLED PORTFOLIO

DECISION SUPPORT

DATA DRIVEN DECISIONS,

PREDICTIVE & PRESCRIPTIVE

SURFACE AND ACT ON DATA

LINK DATA SETS AND DATA ELEMENETS

INCREASE SALES, REDUCE COST

MINIMISE RISK

COMPETITIVE ADVANTAGE


DATA POOL WITH TIERED STORAGE

MASTER REPOSITORY

MARTS / PUDDLES

MARTS / PUDDLES

MARTS / PUDDLES

MARTS / PUDDLES

MARTS / PUDDLES

MARTS / PUDDLES

VIRTUALISED COMPUTE POOL

PRODUCTION LAKE

IN MEMORY

SANDBOX / WORKSPACE

SANDBOX / WORKSPACE

SANDBOX / WORKSPACE

SANDBOX / WORKSPACE

SANDBOX / WORKSPACE

SANDBOX / WORKSPACE

REQUEST PORTAL

DATA CATALOGSALES, CRM, FINANCIAL, ALERTS,

CALL, SOCIAL

TOOLS CATALOGHADOOP, MYSQL, CASSANDRA, R, RSTUDIO, ANACONDA, PYTHON,

JUPYTER

DATA CURATION

DATA GOVERNANCE

META DATA

CONSUMERS

BUSINESS ANALYSTKNOWS THE EXPECTED OUTCOME

QUERIES THE DATAUSES GUI TOOLS

LINE OF BUSINESSREDUCE COST

INCREASE SALESMINIMISE RISK

DATA SCIENTIST EXPLORES THE DATAINGESTS NEW DATA

WRITES SCRIPTS

BUSINESS DATA LAKE SOLUTION VISION

EDW

ELT AA


EMC’S PERSPECTIVE OF THE JOURNEYSTART


STEP 1:


STEP 2:


STEP 3:

IMPLEMENT ANALYTICS

STEP 4:

INTEGRATEAPP DEV

STEP 5:

BUSINESS DATA LAKE


APPSANALYTICS


DATA CURATION

INTEGRATE ALL DATA

LINK DATA SETS AND DATA ELEMENTS

COLLABORATE INTERNALLY &

EXTERNALLY

DRIVE NEW INSIGHTS, REFINE

PROCESSES

IT ENABLED PORTFOLIO

DECISION SUPPORT

DATA DRIVEN DECISIONS,

PREDICTIVE & PRESCRIPTIVE

SURFACE AND ACT ON DATA

LINK DATA SETS AND DATA ELEMENETS

INCREASE SALES, REDUCE COST

MINIMISE RISK

COMPETITIVE ADVANTAGE

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THE BIG DATA, ANALYTICS & APPS JOURNEYSTART – THE INNOVATORS CHALLENGE

CURRENT PHYSICAL HADOOP CLUSTER(S)

AT LEAST ONE HADOOP DISTRIBUTION

DIRECT-ATTACHED STORAGE

STAND-ALONE SERVERS

SINGLE PURPOSE

ALL COMMODITY ENVIRONMENT

TYPICAL HADOOP

SUPPORT AT SCALE

AGILITY

UTILISATION (X3+)

ENTERPRISE GRADE

TYPICAL CHALLENGE


THE BIG DATA, ANALYTICS & APPS JOURNEYSTEP 1 - HADOOP STORAGE CONSOLIDATION AND TIERING

DATA LAKEISILON

(OPERATIONAL)

CURRENT PHYSCIAL HADOOP CLUSTER(S)


MULTI-PROTOCOL NAS SOLUTION

SINGLE FILE SYSTEM THAT SCALES TO PB

NATIVE HDFSINTEGRATION

SEPARATION OF DATA FROM COMPUTE

EFFICIENT DATA PROTECTION

HIGH RESILIENCE AND AVAILABILITY


DATA POINTS

METRIC TRADITIONAL EMC DATA LAKEFTE SUPPORT 1 FTE PER 3 PB STORAGE– 1 FTE FOR 50 PB +

VM/COMPUTE SUPPORT

COMPUTE PERCENTAGE 10% TO 30% TUNABLE WITH SEPARATION OF GROWTH PATHS

TB PER SQ FOOT 62.5TB AT CURRENT CONFIGS 180TB AT CURRENT CONFIGS

REDUNDANCY / UPTIME 3RD PARTY PACKAGE STORAGE LAYER

GROWTH PATH 1 NODE AS NEEDED COMPUTE OR STORAGE AS NEEDED

MANAGEMENT SNMP MIBS ENTERPRISE MONITORING



DATA LAKE AND DATA LAKE EXTENSIONSISILON

(OPERATIONAL)



RACK SCALE FLASH APPLIANCE

PERFORMANCE OF DAS, AVAILABILITY OF SHARED

OBJECT BASED STORAGE WITH HCFS INTERFACE

CLOUD LIKE MGMT, AUTOMATION AND COST

ADVANCED, REAL-TIME ANALYTICS ON HADOOP

HADOOP AT GLOBAL SCALE

DSSD(HI-SPEED ANALYTICS )

ECS(OBJECT & ARCHIVE)



DATA LAKE AND DATA LAKE EXTENSIONSISILON

(OPERATIONAL)



XTREMIO/DSSD(HI-SPEED ANALYTICS )


CLOUD POOLS


THE BIG DATA, ANALYTICS & APPS JOURNEYSTEP 2 – VIRTUALISED HADOOP AS A SERVICE ON A CONVERGED PLATFORM

PRIVATE CLOUD

DATA LAKE AND DATA LAKE EXTENSIONS

COMPUTE: VBLOCK 340 (VNX/XIO)

DSSD(HI-SPEED ANALYTICS )


ISILON(OPERATIONAL)

CLOUD POOLS

VCLOUD AUTOMATION CENTRE + BIG DATA EXTENSIONS



THE BIG DATA, ANALYTICS & APPS JOURNEYSTEP 3 – ADVANCED ANALYTICS

PRIVATE CLOUD


COMPUTE: VBLOCK 340 (VNX)



ISILON(OPERATIONAL)

CLOUD POOLS

VCLOUD AUTOMATION AUTOMATION CENTRE + BIG DATA EXTENSIONS

AT LEAST ONE HADOOP DISTRIBUTION ADVANCED ANALYTICS

DATA SCIENCE

VISUALISATION


THE BIG DATA, ANALYTICS & APPS JOURNEYSTEP 4 – INSIGHT DRIVEN APPLICATIONS

PRIVATE CLOUD





ISILON(OPERATIONAL)

CLOUD POOLS

PLATFORM AS A SERVICE

AT LEAST ONE HADOOP DISTRIBUTION ADVANCED ANALYTICS

DATA SCIENCE

VISUALISATION


THE BIG DATA, ANALYTICS & APPS JOURNEYSTEP 5 – DATA CURATION, DATA GOVERNANCE AND CLOUD LIKE M&A

PLATFORM MANAGER

PRIVATE CLOUD





ISILON(OPERATIONAL)

CLOUD POOLS

DATA CURATOR

ENRICH

INGEST

INDEX

DATA GOVERNOR

LINEAGE

QUALITY

SECURITY

PLATFORM NAVIGATOR ADMINISTRATION ANALYTICS CATALOG DATA CATALOG

AT LEAST ONE HADOOP DISTRIBUTION EXTENSION PACKS

DATA SCIENCER, RStudio, Anaconda python, jupyter

VISUALIZATION

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1. SELECTING THE WRONG USECASES

2. MANAGEMENT RESISTENCE

3. ASKING THE WRONG QUESTIONS

4. LACKING THE RIGHT SKILLS

5. UNANTICIPATED PROBLEMS

6. DIASGREEMENT ON ENTERPRISE STRATEGY

7. BIG DATA SILOS

8. PROBLEM AVOIDANCE

FOR MANY, TECHNOLOGY IS NOT THE PROBLEM

EIGHT REASONS WHY BIG DATA PROJECTS FAIL

LACK OF BUY-IN FROM THE BUSINESS


THE MORE YOU TRY AND UNDERSTAND THE TECHNICALITIES OF ANALYTICS

THE MORE DIFFICULT IT BECOMES


CUSTOMER ANALYTICS360 VIEW OF THE CUSTOMER

OPERATIONAL ANALYTICSANALYSE, PREDICT, OPTIMISE

FRAUD & COMPLIANCE ANALYTICSANTICIPATE, PREVENT, COMPLY

DATA DRIVEN PRODUCTS & SERVICESNEW REVENUE, COMPETITIVE EDGE, LOYALTY


HEALTHCARE ANALYTICSPREVENTION, REALTIME MONITORING

THE ART OF THE POSSIBLE


Align business and IT goals around big

data

Identify strategic

opportunities for big data

analytics

Recommend the appropriate

analytics engagement

and deployment roadmap

1 2 3 4 5

WorkshopExplore Next StepsResearch Interview

Demonstrate the potential value using data science techniques

Prioritize key use cases by

assessing feasibility and

ROI

FINDING THE USE CASE:THE BIG DATA VISION WORKSHOP


THE BIG DATA, ANALYTICS & APPS JOURNEYSTART


STEP 1:


STEP 2:


STEP 3:

IMPLEMENT ANALYTICS

STEP 4:

INTEGRATEAPP DEV

STEP 5:

BUSINESS DATA LAKE


APPSANALYTICS


DATA CURATION

BIG DATA VISIONWORKSHOP

PROOF OF VALUECONSULTINGFAST TRACK

TECHNOLOGY


CONVERGED PLATFORM TO ACCELERATE THE DELIVERY OF BUSINESS OUTCOMESEMC BUSINESS DATA LAKE

INFRASTRUCTURE

SOFTWARE

OPTIONS

FAST TIME TO VALUE | REDUCED RISK | EASE OF USE | ENTERPRISE SCALE | OPEN & EXTENSIBLE

PLATFORM MANAGER

MultiprotocolBig Data ready

DATA GOVERNOR

DATA CURATOR

ENRICH

INGESTPowered by

INDEXPowered by

PRIVATE CLOUD

ISILONDATA LAKE

COMPUTE:EMC Converged Platform Vblock® System 340

HI-SPEED ANALYTICS (XtremIO)HYPERSCALE (ECS)

LINEAGEPowered by

QUALITYPowered by

SECURITYPowered by

PLATFORM NAVIGATOR ADMINISTRATION ANALYTICS CATALOG DATA CATALOG

AT LEAST ONE HADOOP DISTRIBUTION EXTENSION PACKS

DATA SCIENCER, RStudio, Anaconda python, jupyter

VISUALIZATION


EMC BIG DATA PORTFOLIO


MORE INFORMATION?http://www.emc.com/big-data

@thestoragechap

developing a successful big data business strategy

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