analytics, monetization and how to avoid the big data swamp
TRANSCRIPT
0 copy Copyright 2017 FUJITSU
FujitsuForum2017
FujitsuForum
1 copy Copyright 2017 FUJITSU
Analytics monetization and how to avoid the Big Data swamp
Christian Benson
VP Head of Intelligent Enterprise and Applications Transformation EMEIA Fujitsu
Naeem Sarwar
Head of Analytics UKampI Intelligent Enterprise Business and Application Services EMEIA
Albert MercadalHead of Analytics EMEIA Intelligent Enterprise Business and Application Services EMEIA
2 copy Copyright 2017 FUJITSU
All Business Models are Changing
Embracing and Enabling Digital transforms organizations and
business models
3 copy Copyright 2017 FUJITSU
Achieving Successful Digital Transformation
Mastering Business Innovation
Mastering Wellbeing amp Compliance
Mastering Customer
Experience
Enabling Digital
MasteringEnterprise
Productivity
Shaping a better future - together
Experience moments that matter
Operational excellence through
new ways of working
Protecting people reputations and
revenues
4 copy Copyright 2017 FUJITSU
Wave 1 Data Warehousing
Data Management
Data Warehouse
Operational Data Store
Data DeliveryData DeliveryECTML
Exploitation Warehouse
Data Mining Warehouse
OLAP Data Mart
Operational Data Mart
Operational Systems
Financial
LOB
Operational
Sales
Getting Data In Getting Information Out
5 copy Copyright 2017 FUJITSU
On Becoming a Data Graveyard
Built for Reporting and lsquoBIrsquo
Slow build laborious Modelling
Slow Refinements
Limited time to Value
Always out of date
6 copy Copyright 2017 FUJITSU
Wave 2 Enter the Dragon Data Lake
Built for Analytics
Limited Modelling
Rapid Refinements
Short time to Value
Real Time Feeds and Analyses
social media monitoring
churn analysis profitability modellingcustomer profiling regulatory compliance
repo
rtin
g
continuous planning
financial controls management
threat modellingforecasting
regression analysis
opti
miz
atio
n
bu
dg
eting
fraud prediction
segmentationretention planning
propensity modelling
sentiment analysis
das
hb
oard
s
mac
hin
e le
arn
ing
operational risk management
correlation analysisresource optimization
on line recommendations
scenario modelling
demand forecastingkpi management predictive analytics
virtual assistants
scor
ecar
ds
cost analysis
clu
ster
an
alys
is
ad targ
eting
Application
Interactive Web and Mobile Applications
BI Reporting Ad Hoc Analysis
EnterpriseApplications
Hadoop
Gov
ern
ance
an
d In
teg
rati
on Data Access
Data Management
Secu
rity
Op
erat
ion
Data Systems
Sources
OLTP ERP CRM Systems
Documents and Emails
Web LogsClick Streams
Social Networks
MachineGenerated
SensorData
Geo-locationData
Statistical Analysis
7 copy Copyright 2017 FUJITSU
On the making of a Data Swamp
Poorly-defined purpose
Lack of definition of desired analytics
ldquoModel nothingrdquo mentality
Variable data quality
Challenging navigation
Invest on Use Cases without considering ROI
ldquoWithout descriptive metadata and a mechanism to maintain it the data lake is turning into a data swamp And without metadata every subsequent use of data means analysts start from scratchrdquo Source Gartner ldquoBeware the Data Lake Fallacyrdquo
8 copy Copyright 2017 FUJITSU
Wave 3 The Enterprise Data Marketplace
Clearly defined purpose
Clear definition of desired Analytics
Governed and Managed
High levels of data quality
Usable Metadata
Rapid Delivery
Flexible and Adaptive
Adapted from
M
Social Media
IoT Devices and Sensors
Log and Clickstream Data
Enterprise Applications
Mobile Applications
Bots
Streaming
Ai and ml
Cloud storage
Data warehousing
Hadoop Business Users
Data Driven Applications
Business Decision Makers
IT Professionals
DataAnalysts
DataScientists
9 copy Copyright 2017 FUJITSU
Monetizing your Data Assets
New revenue streams through new Business Lines costs reduction through efficiency gains and increase revenue thanks to improving services
CDO reporting to the CEO and Advanced Analytics as a cross-enterprise capability
Defray costs of enterprise Information Management and Business Analytics
Impress investors improve market-to-book corporate valuations Enable competitive differentiation
Became a Platform through strengthening partner supplier and customer relationships
10 copy Copyright 2017 FUJITSU
Analytics as the Engine of Information Monetization
To grow revenues at scale focus needs to be supporting clients derive business value through better and more frequent decisions from 1st party data combined with additional data assets
DescriptiveAnalytics
DiagnosticAnalytics
PredictiveAnalytics
PrescriptiveAnalytics
How can we make it happen
What will happen
Why did it happen
What Happened
Difficulty
Valu
e Imperative
InertiaIn order to lead the transformation from Descriptive to Prescriptive analytics within the organization it is necessary to track and evaluate all the roadmap
Data Value KPIs how data relates with Business Goals
Financial KPIs which is the ROI NPV of the different initiatives
11 copy Copyright 2017 FUJITSU11
Let us help you get there
Business Requirements Delivering ValueQuick Win
Enabling Analytics
Detailed Vision and Roadmap
Use case discovery through identifying
opportunities for increasing revenues
andor gain efficiency
Identify a Quick Win within the
organization in order to deliver value in the
short terms
Detailed roadmap to guide investment and
articulate working streams to scale
Analytics across the organization
Analytics as a core capability
embedding analytics on the exiting and new processes and
services
12 copy Copyright 2017 FUJITSU
Fujitsu Sans Light ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ
0123456789 notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucircuumlyacutethorn
yumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
Fujitsu Sans ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ 0123456789
notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucircuumlyacute
thornyumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
Fujitsu Sans Medium ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ
0123456789 notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucirc
uumlyacutethornyumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
1 copy Copyright 2017 FUJITSU
Analytics monetization and how to avoid the Big Data swamp
Christian Benson
VP Head of Intelligent Enterprise and Applications Transformation EMEIA Fujitsu
Naeem Sarwar
Head of Analytics UKampI Intelligent Enterprise Business and Application Services EMEIA
Albert MercadalHead of Analytics EMEIA Intelligent Enterprise Business and Application Services EMEIA
2 copy Copyright 2017 FUJITSU
All Business Models are Changing
Embracing and Enabling Digital transforms organizations and
business models
3 copy Copyright 2017 FUJITSU
Achieving Successful Digital Transformation
Mastering Business Innovation
Mastering Wellbeing amp Compliance
Mastering Customer
Experience
Enabling Digital
MasteringEnterprise
Productivity
Shaping a better future - together
Experience moments that matter
Operational excellence through
new ways of working
Protecting people reputations and
revenues
4 copy Copyright 2017 FUJITSU
Wave 1 Data Warehousing
Data Management
Data Warehouse
Operational Data Store
Data DeliveryData DeliveryECTML
Exploitation Warehouse
Data Mining Warehouse
OLAP Data Mart
Operational Data Mart
Operational Systems
Financial
LOB
Operational
Sales
Getting Data In Getting Information Out
5 copy Copyright 2017 FUJITSU
On Becoming a Data Graveyard
Built for Reporting and lsquoBIrsquo
Slow build laborious Modelling
Slow Refinements
Limited time to Value
Always out of date
6 copy Copyright 2017 FUJITSU
Wave 2 Enter the Dragon Data Lake
Built for Analytics
Limited Modelling
Rapid Refinements
Short time to Value
Real Time Feeds and Analyses
social media monitoring
churn analysis profitability modellingcustomer profiling regulatory compliance
repo
rtin
g
continuous planning
financial controls management
threat modellingforecasting
regression analysis
opti
miz
atio
n
bu
dg
eting
fraud prediction
segmentationretention planning
propensity modelling
sentiment analysis
das
hb
oard
s
mac
hin
e le
arn
ing
operational risk management
correlation analysisresource optimization
on line recommendations
scenario modelling
demand forecastingkpi management predictive analytics
virtual assistants
scor
ecar
ds
cost analysis
clu
ster
an
alys
is
ad targ
eting
Application
Interactive Web and Mobile Applications
BI Reporting Ad Hoc Analysis
EnterpriseApplications
Hadoop
Gov
ern
ance
an
d In
teg
rati
on Data Access
Data Management
Secu
rity
Op
erat
ion
Data Systems
Sources
OLTP ERP CRM Systems
Documents and Emails
Web LogsClick Streams
Social Networks
MachineGenerated
SensorData
Geo-locationData
Statistical Analysis
7 copy Copyright 2017 FUJITSU
On the making of a Data Swamp
Poorly-defined purpose
Lack of definition of desired analytics
ldquoModel nothingrdquo mentality
Variable data quality
Challenging navigation
Invest on Use Cases without considering ROI
ldquoWithout descriptive metadata and a mechanism to maintain it the data lake is turning into a data swamp And without metadata every subsequent use of data means analysts start from scratchrdquo Source Gartner ldquoBeware the Data Lake Fallacyrdquo
8 copy Copyright 2017 FUJITSU
Wave 3 The Enterprise Data Marketplace
Clearly defined purpose
Clear definition of desired Analytics
Governed and Managed
High levels of data quality
Usable Metadata
Rapid Delivery
Flexible and Adaptive
Adapted from
M
Social Media
IoT Devices and Sensors
Log and Clickstream Data
Enterprise Applications
Mobile Applications
Bots
Streaming
Ai and ml
Cloud storage
Data warehousing
Hadoop Business Users
Data Driven Applications
Business Decision Makers
IT Professionals
DataAnalysts
DataScientists
9 copy Copyright 2017 FUJITSU
Monetizing your Data Assets
New revenue streams through new Business Lines costs reduction through efficiency gains and increase revenue thanks to improving services
CDO reporting to the CEO and Advanced Analytics as a cross-enterprise capability
Defray costs of enterprise Information Management and Business Analytics
Impress investors improve market-to-book corporate valuations Enable competitive differentiation
Became a Platform through strengthening partner supplier and customer relationships
10 copy Copyright 2017 FUJITSU
Analytics as the Engine of Information Monetization
To grow revenues at scale focus needs to be supporting clients derive business value through better and more frequent decisions from 1st party data combined with additional data assets
DescriptiveAnalytics
DiagnosticAnalytics
PredictiveAnalytics
PrescriptiveAnalytics
How can we make it happen
What will happen
Why did it happen
What Happened
Difficulty
Valu
e Imperative
InertiaIn order to lead the transformation from Descriptive to Prescriptive analytics within the organization it is necessary to track and evaluate all the roadmap
Data Value KPIs how data relates with Business Goals
Financial KPIs which is the ROI NPV of the different initiatives
11 copy Copyright 2017 FUJITSU11
Let us help you get there
Business Requirements Delivering ValueQuick Win
Enabling Analytics
Detailed Vision and Roadmap
Use case discovery through identifying
opportunities for increasing revenues
andor gain efficiency
Identify a Quick Win within the
organization in order to deliver value in the
short terms
Detailed roadmap to guide investment and
articulate working streams to scale
Analytics across the organization
Analytics as a core capability
embedding analytics on the exiting and new processes and
services
12 copy Copyright 2017 FUJITSU
Fujitsu Sans Light ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ
0123456789 notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucircuumlyacutethorn
yumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
Fujitsu Sans ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ 0123456789
notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucircuumlyacute
thornyumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
Fujitsu Sans Medium ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ
0123456789 notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucirc
uumlyacutethornyumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
2 copy Copyright 2017 FUJITSU
All Business Models are Changing
Embracing and Enabling Digital transforms organizations and
business models
3 copy Copyright 2017 FUJITSU
Achieving Successful Digital Transformation
Mastering Business Innovation
Mastering Wellbeing amp Compliance
Mastering Customer
Experience
Enabling Digital
MasteringEnterprise
Productivity
Shaping a better future - together
Experience moments that matter
Operational excellence through
new ways of working
Protecting people reputations and
revenues
4 copy Copyright 2017 FUJITSU
Wave 1 Data Warehousing
Data Management
Data Warehouse
Operational Data Store
Data DeliveryData DeliveryECTML
Exploitation Warehouse
Data Mining Warehouse
OLAP Data Mart
Operational Data Mart
Operational Systems
Financial
LOB
Operational
Sales
Getting Data In Getting Information Out
5 copy Copyright 2017 FUJITSU
On Becoming a Data Graveyard
Built for Reporting and lsquoBIrsquo
Slow build laborious Modelling
Slow Refinements
Limited time to Value
Always out of date
6 copy Copyright 2017 FUJITSU
Wave 2 Enter the Dragon Data Lake
Built for Analytics
Limited Modelling
Rapid Refinements
Short time to Value
Real Time Feeds and Analyses
social media monitoring
churn analysis profitability modellingcustomer profiling regulatory compliance
repo
rtin
g
continuous planning
financial controls management
threat modellingforecasting
regression analysis
opti
miz
atio
n
bu
dg
eting
fraud prediction
segmentationretention planning
propensity modelling
sentiment analysis
das
hb
oard
s
mac
hin
e le
arn
ing
operational risk management
correlation analysisresource optimization
on line recommendations
scenario modelling
demand forecastingkpi management predictive analytics
virtual assistants
scor
ecar
ds
cost analysis
clu
ster
an
alys
is
ad targ
eting
Application
Interactive Web and Mobile Applications
BI Reporting Ad Hoc Analysis
EnterpriseApplications
Hadoop
Gov
ern
ance
an
d In
teg
rati
on Data Access
Data Management
Secu
rity
Op
erat
ion
Data Systems
Sources
OLTP ERP CRM Systems
Documents and Emails
Web LogsClick Streams
Social Networks
MachineGenerated
SensorData
Geo-locationData
Statistical Analysis
7 copy Copyright 2017 FUJITSU
On the making of a Data Swamp
Poorly-defined purpose
Lack of definition of desired analytics
ldquoModel nothingrdquo mentality
Variable data quality
Challenging navigation
Invest on Use Cases without considering ROI
ldquoWithout descriptive metadata and a mechanism to maintain it the data lake is turning into a data swamp And without metadata every subsequent use of data means analysts start from scratchrdquo Source Gartner ldquoBeware the Data Lake Fallacyrdquo
8 copy Copyright 2017 FUJITSU
Wave 3 The Enterprise Data Marketplace
Clearly defined purpose
Clear definition of desired Analytics
Governed and Managed
High levels of data quality
Usable Metadata
Rapid Delivery
Flexible and Adaptive
Adapted from
M
Social Media
IoT Devices and Sensors
Log and Clickstream Data
Enterprise Applications
Mobile Applications
Bots
Streaming
Ai and ml
Cloud storage
Data warehousing
Hadoop Business Users
Data Driven Applications
Business Decision Makers
IT Professionals
DataAnalysts
DataScientists
9 copy Copyright 2017 FUJITSU
Monetizing your Data Assets
New revenue streams through new Business Lines costs reduction through efficiency gains and increase revenue thanks to improving services
CDO reporting to the CEO and Advanced Analytics as a cross-enterprise capability
Defray costs of enterprise Information Management and Business Analytics
Impress investors improve market-to-book corporate valuations Enable competitive differentiation
Became a Platform through strengthening partner supplier and customer relationships
10 copy Copyright 2017 FUJITSU
Analytics as the Engine of Information Monetization
To grow revenues at scale focus needs to be supporting clients derive business value through better and more frequent decisions from 1st party data combined with additional data assets
DescriptiveAnalytics
DiagnosticAnalytics
PredictiveAnalytics
PrescriptiveAnalytics
How can we make it happen
What will happen
Why did it happen
What Happened
Difficulty
Valu
e Imperative
InertiaIn order to lead the transformation from Descriptive to Prescriptive analytics within the organization it is necessary to track and evaluate all the roadmap
Data Value KPIs how data relates with Business Goals
Financial KPIs which is the ROI NPV of the different initiatives
11 copy Copyright 2017 FUJITSU11
Let us help you get there
Business Requirements Delivering ValueQuick Win
Enabling Analytics
Detailed Vision and Roadmap
Use case discovery through identifying
opportunities for increasing revenues
andor gain efficiency
Identify a Quick Win within the
organization in order to deliver value in the
short terms
Detailed roadmap to guide investment and
articulate working streams to scale
Analytics across the organization
Analytics as a core capability
embedding analytics on the exiting and new processes and
services
12 copy Copyright 2017 FUJITSU
Fujitsu Sans Light ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ
0123456789 notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucircuumlyacutethorn
yumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
Fujitsu Sans ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ 0123456789
notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucircuumlyacute
thornyumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
Fujitsu Sans Medium ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ
0123456789 notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucirc
uumlyacutethornyumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
3 copy Copyright 2017 FUJITSU
Achieving Successful Digital Transformation
Mastering Business Innovation
Mastering Wellbeing amp Compliance
Mastering Customer
Experience
Enabling Digital
MasteringEnterprise
Productivity
Shaping a better future - together
Experience moments that matter
Operational excellence through
new ways of working
Protecting people reputations and
revenues
4 copy Copyright 2017 FUJITSU
Wave 1 Data Warehousing
Data Management
Data Warehouse
Operational Data Store
Data DeliveryData DeliveryECTML
Exploitation Warehouse
Data Mining Warehouse
OLAP Data Mart
Operational Data Mart
Operational Systems
Financial
LOB
Operational
Sales
Getting Data In Getting Information Out
5 copy Copyright 2017 FUJITSU
On Becoming a Data Graveyard
Built for Reporting and lsquoBIrsquo
Slow build laborious Modelling
Slow Refinements
Limited time to Value
Always out of date
6 copy Copyright 2017 FUJITSU
Wave 2 Enter the Dragon Data Lake
Built for Analytics
Limited Modelling
Rapid Refinements
Short time to Value
Real Time Feeds and Analyses
social media monitoring
churn analysis profitability modellingcustomer profiling regulatory compliance
repo
rtin
g
continuous planning
financial controls management
threat modellingforecasting
regression analysis
opti
miz
atio
n
bu
dg
eting
fraud prediction
segmentationretention planning
propensity modelling
sentiment analysis
das
hb
oard
s
mac
hin
e le
arn
ing
operational risk management
correlation analysisresource optimization
on line recommendations
scenario modelling
demand forecastingkpi management predictive analytics
virtual assistants
scor
ecar
ds
cost analysis
clu
ster
an
alys
is
ad targ
eting
Application
Interactive Web and Mobile Applications
BI Reporting Ad Hoc Analysis
EnterpriseApplications
Hadoop
Gov
ern
ance
an
d In
teg
rati
on Data Access
Data Management
Secu
rity
Op
erat
ion
Data Systems
Sources
OLTP ERP CRM Systems
Documents and Emails
Web LogsClick Streams
Social Networks
MachineGenerated
SensorData
Geo-locationData
Statistical Analysis
7 copy Copyright 2017 FUJITSU
On the making of a Data Swamp
Poorly-defined purpose
Lack of definition of desired analytics
ldquoModel nothingrdquo mentality
Variable data quality
Challenging navigation
Invest on Use Cases without considering ROI
ldquoWithout descriptive metadata and a mechanism to maintain it the data lake is turning into a data swamp And without metadata every subsequent use of data means analysts start from scratchrdquo Source Gartner ldquoBeware the Data Lake Fallacyrdquo
8 copy Copyright 2017 FUJITSU
Wave 3 The Enterprise Data Marketplace
Clearly defined purpose
Clear definition of desired Analytics
Governed and Managed
High levels of data quality
Usable Metadata
Rapid Delivery
Flexible and Adaptive
Adapted from
M
Social Media
IoT Devices and Sensors
Log and Clickstream Data
Enterprise Applications
Mobile Applications
Bots
Streaming
Ai and ml
Cloud storage
Data warehousing
Hadoop Business Users
Data Driven Applications
Business Decision Makers
IT Professionals
DataAnalysts
DataScientists
9 copy Copyright 2017 FUJITSU
Monetizing your Data Assets
New revenue streams through new Business Lines costs reduction through efficiency gains and increase revenue thanks to improving services
CDO reporting to the CEO and Advanced Analytics as a cross-enterprise capability
Defray costs of enterprise Information Management and Business Analytics
Impress investors improve market-to-book corporate valuations Enable competitive differentiation
Became a Platform through strengthening partner supplier and customer relationships
10 copy Copyright 2017 FUJITSU
Analytics as the Engine of Information Monetization
To grow revenues at scale focus needs to be supporting clients derive business value through better and more frequent decisions from 1st party data combined with additional data assets
DescriptiveAnalytics
DiagnosticAnalytics
PredictiveAnalytics
PrescriptiveAnalytics
How can we make it happen
What will happen
Why did it happen
What Happened
Difficulty
Valu
e Imperative
InertiaIn order to lead the transformation from Descriptive to Prescriptive analytics within the organization it is necessary to track and evaluate all the roadmap
Data Value KPIs how data relates with Business Goals
Financial KPIs which is the ROI NPV of the different initiatives
11 copy Copyright 2017 FUJITSU11
Let us help you get there
Business Requirements Delivering ValueQuick Win
Enabling Analytics
Detailed Vision and Roadmap
Use case discovery through identifying
opportunities for increasing revenues
andor gain efficiency
Identify a Quick Win within the
organization in order to deliver value in the
short terms
Detailed roadmap to guide investment and
articulate working streams to scale
Analytics across the organization
Analytics as a core capability
embedding analytics on the exiting and new processes and
services
12 copy Copyright 2017 FUJITSU
Fujitsu Sans Light ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ
0123456789 notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucircuumlyacutethorn
yumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
Fujitsu Sans ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ 0123456789
notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucircuumlyacute
thornyumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
Fujitsu Sans Medium ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ
0123456789 notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucirc
uumlyacutethornyumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
4 copy Copyright 2017 FUJITSU
Wave 1 Data Warehousing
Data Management
Data Warehouse
Operational Data Store
Data DeliveryData DeliveryECTML
Exploitation Warehouse
Data Mining Warehouse
OLAP Data Mart
Operational Data Mart
Operational Systems
Financial
LOB
Operational
Sales
Getting Data In Getting Information Out
5 copy Copyright 2017 FUJITSU
On Becoming a Data Graveyard
Built for Reporting and lsquoBIrsquo
Slow build laborious Modelling
Slow Refinements
Limited time to Value
Always out of date
6 copy Copyright 2017 FUJITSU
Wave 2 Enter the Dragon Data Lake
Built for Analytics
Limited Modelling
Rapid Refinements
Short time to Value
Real Time Feeds and Analyses
social media monitoring
churn analysis profitability modellingcustomer profiling regulatory compliance
repo
rtin
g
continuous planning
financial controls management
threat modellingforecasting
regression analysis
opti
miz
atio
n
bu
dg
eting
fraud prediction
segmentationretention planning
propensity modelling
sentiment analysis
das
hb
oard
s
mac
hin
e le
arn
ing
operational risk management
correlation analysisresource optimization
on line recommendations
scenario modelling
demand forecastingkpi management predictive analytics
virtual assistants
scor
ecar
ds
cost analysis
clu
ster
an
alys
is
ad targ
eting
Application
Interactive Web and Mobile Applications
BI Reporting Ad Hoc Analysis
EnterpriseApplications
Hadoop
Gov
ern
ance
an
d In
teg
rati
on Data Access
Data Management
Secu
rity
Op
erat
ion
Data Systems
Sources
OLTP ERP CRM Systems
Documents and Emails
Web LogsClick Streams
Social Networks
MachineGenerated
SensorData
Geo-locationData
Statistical Analysis
7 copy Copyright 2017 FUJITSU
On the making of a Data Swamp
Poorly-defined purpose
Lack of definition of desired analytics
ldquoModel nothingrdquo mentality
Variable data quality
Challenging navigation
Invest on Use Cases without considering ROI
ldquoWithout descriptive metadata and a mechanism to maintain it the data lake is turning into a data swamp And without metadata every subsequent use of data means analysts start from scratchrdquo Source Gartner ldquoBeware the Data Lake Fallacyrdquo
8 copy Copyright 2017 FUJITSU
Wave 3 The Enterprise Data Marketplace
Clearly defined purpose
Clear definition of desired Analytics
Governed and Managed
High levels of data quality
Usable Metadata
Rapid Delivery
Flexible and Adaptive
Adapted from
M
Social Media
IoT Devices and Sensors
Log and Clickstream Data
Enterprise Applications
Mobile Applications
Bots
Streaming
Ai and ml
Cloud storage
Data warehousing
Hadoop Business Users
Data Driven Applications
Business Decision Makers
IT Professionals
DataAnalysts
DataScientists
9 copy Copyright 2017 FUJITSU
Monetizing your Data Assets
New revenue streams through new Business Lines costs reduction through efficiency gains and increase revenue thanks to improving services
CDO reporting to the CEO and Advanced Analytics as a cross-enterprise capability
Defray costs of enterprise Information Management and Business Analytics
Impress investors improve market-to-book corporate valuations Enable competitive differentiation
Became a Platform through strengthening partner supplier and customer relationships
10 copy Copyright 2017 FUJITSU
Analytics as the Engine of Information Monetization
To grow revenues at scale focus needs to be supporting clients derive business value through better and more frequent decisions from 1st party data combined with additional data assets
DescriptiveAnalytics
DiagnosticAnalytics
PredictiveAnalytics
PrescriptiveAnalytics
How can we make it happen
What will happen
Why did it happen
What Happened
Difficulty
Valu
e Imperative
InertiaIn order to lead the transformation from Descriptive to Prescriptive analytics within the organization it is necessary to track and evaluate all the roadmap
Data Value KPIs how data relates with Business Goals
Financial KPIs which is the ROI NPV of the different initiatives
11 copy Copyright 2017 FUJITSU11
Let us help you get there
Business Requirements Delivering ValueQuick Win
Enabling Analytics
Detailed Vision and Roadmap
Use case discovery through identifying
opportunities for increasing revenues
andor gain efficiency
Identify a Quick Win within the
organization in order to deliver value in the
short terms
Detailed roadmap to guide investment and
articulate working streams to scale
Analytics across the organization
Analytics as a core capability
embedding analytics on the exiting and new processes and
services
12 copy Copyright 2017 FUJITSU
Fujitsu Sans Light ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ
0123456789 notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucircuumlyacutethorn
yumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
Fujitsu Sans ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ 0123456789
notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucircuumlyacute
thornyumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
Fujitsu Sans Medium ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ
0123456789 notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucirc
uumlyacutethornyumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
5 copy Copyright 2017 FUJITSU
On Becoming a Data Graveyard
Built for Reporting and lsquoBIrsquo
Slow build laborious Modelling
Slow Refinements
Limited time to Value
Always out of date
6 copy Copyright 2017 FUJITSU
Wave 2 Enter the Dragon Data Lake
Built for Analytics
Limited Modelling
Rapid Refinements
Short time to Value
Real Time Feeds and Analyses
social media monitoring
churn analysis profitability modellingcustomer profiling regulatory compliance
repo
rtin
g
continuous planning
financial controls management
threat modellingforecasting
regression analysis
opti
miz
atio
n
bu
dg
eting
fraud prediction
segmentationretention planning
propensity modelling
sentiment analysis
das
hb
oard
s
mac
hin
e le
arn
ing
operational risk management
correlation analysisresource optimization
on line recommendations
scenario modelling
demand forecastingkpi management predictive analytics
virtual assistants
scor
ecar
ds
cost analysis
clu
ster
an
alys
is
ad targ
eting
Application
Interactive Web and Mobile Applications
BI Reporting Ad Hoc Analysis
EnterpriseApplications
Hadoop
Gov
ern
ance
an
d In
teg
rati
on Data Access
Data Management
Secu
rity
Op
erat
ion
Data Systems
Sources
OLTP ERP CRM Systems
Documents and Emails
Web LogsClick Streams
Social Networks
MachineGenerated
SensorData
Geo-locationData
Statistical Analysis
7 copy Copyright 2017 FUJITSU
On the making of a Data Swamp
Poorly-defined purpose
Lack of definition of desired analytics
ldquoModel nothingrdquo mentality
Variable data quality
Challenging navigation
Invest on Use Cases without considering ROI
ldquoWithout descriptive metadata and a mechanism to maintain it the data lake is turning into a data swamp And without metadata every subsequent use of data means analysts start from scratchrdquo Source Gartner ldquoBeware the Data Lake Fallacyrdquo
8 copy Copyright 2017 FUJITSU
Wave 3 The Enterprise Data Marketplace
Clearly defined purpose
Clear definition of desired Analytics
Governed and Managed
High levels of data quality
Usable Metadata
Rapid Delivery
Flexible and Adaptive
Adapted from
M
Social Media
IoT Devices and Sensors
Log and Clickstream Data
Enterprise Applications
Mobile Applications
Bots
Streaming
Ai and ml
Cloud storage
Data warehousing
Hadoop Business Users
Data Driven Applications
Business Decision Makers
IT Professionals
DataAnalysts
DataScientists
9 copy Copyright 2017 FUJITSU
Monetizing your Data Assets
New revenue streams through new Business Lines costs reduction through efficiency gains and increase revenue thanks to improving services
CDO reporting to the CEO and Advanced Analytics as a cross-enterprise capability
Defray costs of enterprise Information Management and Business Analytics
Impress investors improve market-to-book corporate valuations Enable competitive differentiation
Became a Platform through strengthening partner supplier and customer relationships
10 copy Copyright 2017 FUJITSU
Analytics as the Engine of Information Monetization
To grow revenues at scale focus needs to be supporting clients derive business value through better and more frequent decisions from 1st party data combined with additional data assets
DescriptiveAnalytics
DiagnosticAnalytics
PredictiveAnalytics
PrescriptiveAnalytics
How can we make it happen
What will happen
Why did it happen
What Happened
Difficulty
Valu
e Imperative
InertiaIn order to lead the transformation from Descriptive to Prescriptive analytics within the organization it is necessary to track and evaluate all the roadmap
Data Value KPIs how data relates with Business Goals
Financial KPIs which is the ROI NPV of the different initiatives
11 copy Copyright 2017 FUJITSU11
Let us help you get there
Business Requirements Delivering ValueQuick Win
Enabling Analytics
Detailed Vision and Roadmap
Use case discovery through identifying
opportunities for increasing revenues
andor gain efficiency
Identify a Quick Win within the
organization in order to deliver value in the
short terms
Detailed roadmap to guide investment and
articulate working streams to scale
Analytics across the organization
Analytics as a core capability
embedding analytics on the exiting and new processes and
services
12 copy Copyright 2017 FUJITSU
Fujitsu Sans Light ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ
0123456789 notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucircuumlyacutethorn
yumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
Fujitsu Sans ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ 0123456789
notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucircuumlyacute
thornyumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
Fujitsu Sans Medium ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ
0123456789 notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucirc
uumlyacutethornyumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
6 copy Copyright 2017 FUJITSU
Wave 2 Enter the Dragon Data Lake
Built for Analytics
Limited Modelling
Rapid Refinements
Short time to Value
Real Time Feeds and Analyses
social media monitoring
churn analysis profitability modellingcustomer profiling regulatory compliance
repo
rtin
g
continuous planning
financial controls management
threat modellingforecasting
regression analysis
opti
miz
atio
n
bu
dg
eting
fraud prediction
segmentationretention planning
propensity modelling
sentiment analysis
das
hb
oard
s
mac
hin
e le
arn
ing
operational risk management
correlation analysisresource optimization
on line recommendations
scenario modelling
demand forecastingkpi management predictive analytics
virtual assistants
scor
ecar
ds
cost analysis
clu
ster
an
alys
is
ad targ
eting
Application
Interactive Web and Mobile Applications
BI Reporting Ad Hoc Analysis
EnterpriseApplications
Hadoop
Gov
ern
ance
an
d In
teg
rati
on Data Access
Data Management
Secu
rity
Op
erat
ion
Data Systems
Sources
OLTP ERP CRM Systems
Documents and Emails
Web LogsClick Streams
Social Networks
MachineGenerated
SensorData
Geo-locationData
Statistical Analysis
7 copy Copyright 2017 FUJITSU
On the making of a Data Swamp
Poorly-defined purpose
Lack of definition of desired analytics
ldquoModel nothingrdquo mentality
Variable data quality
Challenging navigation
Invest on Use Cases without considering ROI
ldquoWithout descriptive metadata and a mechanism to maintain it the data lake is turning into a data swamp And without metadata every subsequent use of data means analysts start from scratchrdquo Source Gartner ldquoBeware the Data Lake Fallacyrdquo
8 copy Copyright 2017 FUJITSU
Wave 3 The Enterprise Data Marketplace
Clearly defined purpose
Clear definition of desired Analytics
Governed and Managed
High levels of data quality
Usable Metadata
Rapid Delivery
Flexible and Adaptive
Adapted from
M
Social Media
IoT Devices and Sensors
Log and Clickstream Data
Enterprise Applications
Mobile Applications
Bots
Streaming
Ai and ml
Cloud storage
Data warehousing
Hadoop Business Users
Data Driven Applications
Business Decision Makers
IT Professionals
DataAnalysts
DataScientists
9 copy Copyright 2017 FUJITSU
Monetizing your Data Assets
New revenue streams through new Business Lines costs reduction through efficiency gains and increase revenue thanks to improving services
CDO reporting to the CEO and Advanced Analytics as a cross-enterprise capability
Defray costs of enterprise Information Management and Business Analytics
Impress investors improve market-to-book corporate valuations Enable competitive differentiation
Became a Platform through strengthening partner supplier and customer relationships
10 copy Copyright 2017 FUJITSU
Analytics as the Engine of Information Monetization
To grow revenues at scale focus needs to be supporting clients derive business value through better and more frequent decisions from 1st party data combined with additional data assets
DescriptiveAnalytics
DiagnosticAnalytics
PredictiveAnalytics
PrescriptiveAnalytics
How can we make it happen
What will happen
Why did it happen
What Happened
Difficulty
Valu
e Imperative
InertiaIn order to lead the transformation from Descriptive to Prescriptive analytics within the organization it is necessary to track and evaluate all the roadmap
Data Value KPIs how data relates with Business Goals
Financial KPIs which is the ROI NPV of the different initiatives
11 copy Copyright 2017 FUJITSU11
Let us help you get there
Business Requirements Delivering ValueQuick Win
Enabling Analytics
Detailed Vision and Roadmap
Use case discovery through identifying
opportunities for increasing revenues
andor gain efficiency
Identify a Quick Win within the
organization in order to deliver value in the
short terms
Detailed roadmap to guide investment and
articulate working streams to scale
Analytics across the organization
Analytics as a core capability
embedding analytics on the exiting and new processes and
services
12 copy Copyright 2017 FUJITSU
Fujitsu Sans Light ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ
0123456789 notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucircuumlyacutethorn
yumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
Fujitsu Sans ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ 0123456789
notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucircuumlyacute
thornyumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
Fujitsu Sans Medium ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ
0123456789 notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucirc
uumlyacutethornyumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
7 copy Copyright 2017 FUJITSU
On the making of a Data Swamp
Poorly-defined purpose
Lack of definition of desired analytics
ldquoModel nothingrdquo mentality
Variable data quality
Challenging navigation
Invest on Use Cases without considering ROI
ldquoWithout descriptive metadata and a mechanism to maintain it the data lake is turning into a data swamp And without metadata every subsequent use of data means analysts start from scratchrdquo Source Gartner ldquoBeware the Data Lake Fallacyrdquo
8 copy Copyright 2017 FUJITSU
Wave 3 The Enterprise Data Marketplace
Clearly defined purpose
Clear definition of desired Analytics
Governed and Managed
High levels of data quality
Usable Metadata
Rapid Delivery
Flexible and Adaptive
Adapted from
M
Social Media
IoT Devices and Sensors
Log and Clickstream Data
Enterprise Applications
Mobile Applications
Bots
Streaming
Ai and ml
Cloud storage
Data warehousing
Hadoop Business Users
Data Driven Applications
Business Decision Makers
IT Professionals
DataAnalysts
DataScientists
9 copy Copyright 2017 FUJITSU
Monetizing your Data Assets
New revenue streams through new Business Lines costs reduction through efficiency gains and increase revenue thanks to improving services
CDO reporting to the CEO and Advanced Analytics as a cross-enterprise capability
Defray costs of enterprise Information Management and Business Analytics
Impress investors improve market-to-book corporate valuations Enable competitive differentiation
Became a Platform through strengthening partner supplier and customer relationships
10 copy Copyright 2017 FUJITSU
Analytics as the Engine of Information Monetization
To grow revenues at scale focus needs to be supporting clients derive business value through better and more frequent decisions from 1st party data combined with additional data assets
DescriptiveAnalytics
DiagnosticAnalytics
PredictiveAnalytics
PrescriptiveAnalytics
How can we make it happen
What will happen
Why did it happen
What Happened
Difficulty
Valu
e Imperative
InertiaIn order to lead the transformation from Descriptive to Prescriptive analytics within the organization it is necessary to track and evaluate all the roadmap
Data Value KPIs how data relates with Business Goals
Financial KPIs which is the ROI NPV of the different initiatives
11 copy Copyright 2017 FUJITSU11
Let us help you get there
Business Requirements Delivering ValueQuick Win
Enabling Analytics
Detailed Vision and Roadmap
Use case discovery through identifying
opportunities for increasing revenues
andor gain efficiency
Identify a Quick Win within the
organization in order to deliver value in the
short terms
Detailed roadmap to guide investment and
articulate working streams to scale
Analytics across the organization
Analytics as a core capability
embedding analytics on the exiting and new processes and
services
12 copy Copyright 2017 FUJITSU
Fujitsu Sans Light ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ
0123456789 notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucircuumlyacutethorn
yumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
Fujitsu Sans ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ 0123456789
notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucircuumlyacute
thornyumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
Fujitsu Sans Medium ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ
0123456789 notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucirc
uumlyacutethornyumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
8 copy Copyright 2017 FUJITSU
Wave 3 The Enterprise Data Marketplace
Clearly defined purpose
Clear definition of desired Analytics
Governed and Managed
High levels of data quality
Usable Metadata
Rapid Delivery
Flexible and Adaptive
Adapted from
M
Social Media
IoT Devices and Sensors
Log and Clickstream Data
Enterprise Applications
Mobile Applications
Bots
Streaming
Ai and ml
Cloud storage
Data warehousing
Hadoop Business Users
Data Driven Applications
Business Decision Makers
IT Professionals
DataAnalysts
DataScientists
9 copy Copyright 2017 FUJITSU
Monetizing your Data Assets
New revenue streams through new Business Lines costs reduction through efficiency gains and increase revenue thanks to improving services
CDO reporting to the CEO and Advanced Analytics as a cross-enterprise capability
Defray costs of enterprise Information Management and Business Analytics
Impress investors improve market-to-book corporate valuations Enable competitive differentiation
Became a Platform through strengthening partner supplier and customer relationships
10 copy Copyright 2017 FUJITSU
Analytics as the Engine of Information Monetization
To grow revenues at scale focus needs to be supporting clients derive business value through better and more frequent decisions from 1st party data combined with additional data assets
DescriptiveAnalytics
DiagnosticAnalytics
PredictiveAnalytics
PrescriptiveAnalytics
How can we make it happen
What will happen
Why did it happen
What Happened
Difficulty
Valu
e Imperative
InertiaIn order to lead the transformation from Descriptive to Prescriptive analytics within the organization it is necessary to track and evaluate all the roadmap
Data Value KPIs how data relates with Business Goals
Financial KPIs which is the ROI NPV of the different initiatives
11 copy Copyright 2017 FUJITSU11
Let us help you get there
Business Requirements Delivering ValueQuick Win
Enabling Analytics
Detailed Vision and Roadmap
Use case discovery through identifying
opportunities for increasing revenues
andor gain efficiency
Identify a Quick Win within the
organization in order to deliver value in the
short terms
Detailed roadmap to guide investment and
articulate working streams to scale
Analytics across the organization
Analytics as a core capability
embedding analytics on the exiting and new processes and
services
12 copy Copyright 2017 FUJITSU
Fujitsu Sans Light ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ
0123456789 notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucircuumlyacutethorn
yumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
Fujitsu Sans ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ 0123456789
notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucircuumlyacute
thornyumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
Fujitsu Sans Medium ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ
0123456789 notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucirc
uumlyacutethornyumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
9 copy Copyright 2017 FUJITSU
Monetizing your Data Assets
New revenue streams through new Business Lines costs reduction through efficiency gains and increase revenue thanks to improving services
CDO reporting to the CEO and Advanced Analytics as a cross-enterprise capability
Defray costs of enterprise Information Management and Business Analytics
Impress investors improve market-to-book corporate valuations Enable competitive differentiation
Became a Platform through strengthening partner supplier and customer relationships
10 copy Copyright 2017 FUJITSU
Analytics as the Engine of Information Monetization
To grow revenues at scale focus needs to be supporting clients derive business value through better and more frequent decisions from 1st party data combined with additional data assets
DescriptiveAnalytics
DiagnosticAnalytics
PredictiveAnalytics
PrescriptiveAnalytics
How can we make it happen
What will happen
Why did it happen
What Happened
Difficulty
Valu
e Imperative
InertiaIn order to lead the transformation from Descriptive to Prescriptive analytics within the organization it is necessary to track and evaluate all the roadmap
Data Value KPIs how data relates with Business Goals
Financial KPIs which is the ROI NPV of the different initiatives
11 copy Copyright 2017 FUJITSU11
Let us help you get there
Business Requirements Delivering ValueQuick Win
Enabling Analytics
Detailed Vision and Roadmap
Use case discovery through identifying
opportunities for increasing revenues
andor gain efficiency
Identify a Quick Win within the
organization in order to deliver value in the
short terms
Detailed roadmap to guide investment and
articulate working streams to scale
Analytics across the organization
Analytics as a core capability
embedding analytics on the exiting and new processes and
services
12 copy Copyright 2017 FUJITSU
Fujitsu Sans Light ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ
0123456789 notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucircuumlyacutethorn
yumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
Fujitsu Sans ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ 0123456789
notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucircuumlyacute
thornyumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
Fujitsu Sans Medium ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ
0123456789 notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucirc
uumlyacutethornyumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
10 copy Copyright 2017 FUJITSU
Analytics as the Engine of Information Monetization
To grow revenues at scale focus needs to be supporting clients derive business value through better and more frequent decisions from 1st party data combined with additional data assets
DescriptiveAnalytics
DiagnosticAnalytics
PredictiveAnalytics
PrescriptiveAnalytics
How can we make it happen
What will happen
Why did it happen
What Happened
Difficulty
Valu
e Imperative
InertiaIn order to lead the transformation from Descriptive to Prescriptive analytics within the organization it is necessary to track and evaluate all the roadmap
Data Value KPIs how data relates with Business Goals
Financial KPIs which is the ROI NPV of the different initiatives
11 copy Copyright 2017 FUJITSU11
Let us help you get there
Business Requirements Delivering ValueQuick Win
Enabling Analytics
Detailed Vision and Roadmap
Use case discovery through identifying
opportunities for increasing revenues
andor gain efficiency
Identify a Quick Win within the
organization in order to deliver value in the
short terms
Detailed roadmap to guide investment and
articulate working streams to scale
Analytics across the organization
Analytics as a core capability
embedding analytics on the exiting and new processes and
services
12 copy Copyright 2017 FUJITSU
Fujitsu Sans Light ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ
0123456789 notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucircuumlyacutethorn
yumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
Fujitsu Sans ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ 0123456789
notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucircuumlyacute
thornyumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
Fujitsu Sans Medium ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ
0123456789 notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucirc
uumlyacutethornyumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
11 copy Copyright 2017 FUJITSU11
Let us help you get there
Business Requirements Delivering ValueQuick Win
Enabling Analytics
Detailed Vision and Roadmap
Use case discovery through identifying
opportunities for increasing revenues
andor gain efficiency
Identify a Quick Win within the
organization in order to deliver value in the
short terms
Detailed roadmap to guide investment and
articulate working streams to scale
Analytics across the organization
Analytics as a core capability
embedding analytics on the exiting and new processes and
services
12 copy Copyright 2017 FUJITSU
Fujitsu Sans Light ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ
0123456789 notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucircuumlyacutethorn
yumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
Fujitsu Sans ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ 0123456789
notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucircuumlyacute
thornyumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
Fujitsu Sans Medium ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ
0123456789 notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucirc
uumlyacutethornyumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
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Fujitsu Sans Light ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ
0123456789 notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucircuumlyacutethorn
yumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
Fujitsu Sans ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ 0123456789
notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucircuumlyacute
thornyumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl
Fujitsu Sans Medium ndash abcdefghijklmnopqrstuvwxyz ABCDEFGHIJKLMNOPQRSTUVWXYZ
0123456789 notrdquopound$^amp()_+-=[]rsquo~ltgt| copyuml~iexclcentcurrenyenbrvbarsectumlordflaquoraquonot-
regmacrdegplusmnsup2sup3microparamiddotcedilsup1ordmfrac14frac12frac34iquestAgraveAacuteAcircAtildeAumlAringCcedilEgraveAEligEacuteEcircEumlIgraveIacuteIcircIumlETHNtildeOgraveOacuteOcircOtildeOumltimesOslashUgraveUacuteUcircUumlYacuteTHORNszligagraveaacuteacircatildeaumlaringaeligccedilegraveeacuteecirceumligraveiacuteicirciumlethntildeograveoacuteocircotildeoumldivideoslashugraveuacuteucirc
uumlyacutethornyumlĐıŒœŠšŸŽžƒʼˆˇˉ˙˚˛˜˝-‒ndashmdash―lsquorsquosbquoldquordquobdquodaggerDaggerbullhellippermillsaquorsaquoolinefrasl⁰⁴⁵⁶⁷⁸⁹₀₁₂₃₄₅₆₇₈₉eurotradeΩrarrpart∆prodsumminusradicinfinintasympnelegesdotlozfifl