cloud computing, big data and mobile enhancing innovation through busine

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Central Connecticut State University School of Business Spring 2014 Spring 2013 © 2013-2014 Michael Gendron 1 Cloud Computing, Big Data and Mobile: Enhancing Innovation Through Business Intelligence Michael Gendron 6/4/2014

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Technology is integrated into the DNA of business and of society itself. Some of the most recent entrants are Cloud Computing, Big Data, and Mobile. By putting these technologies together, we arrive at an intersection that creates a “sweet spot” where innovation can be enhanced within your organization. This session will put those pieces together and give you tools to move your organization toward that sweet spot. Speaker: Michael Gendron, Professor, Central CT State University

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Page 1: Cloud computing, big data and mobile enhancing innovation through busine

Central Connecticut State University School of Business

Spring 2014

Spring 2013

© 2013-2014 Michael Gendron 1

Cloud Computing, Big Data and Mobile: Enhancing Innovation Through Business Intelligence

Michael Gendron

6/4/2014

Page 2: Cloud computing, big data and mobile enhancing innovation through busine

Central Connecticut State University School of Business

Enabling Innovation at the BI Sweet Spot THE BI ECOSYSTEM

6/4/2014 © 2013-2014 Michael Gendron 2

Page 3: Cloud computing, big data and mobile enhancing innovation through busine

Central Connecticut State University School of Business

Agenda • Background

– The Cloud Ecosystem

– Big Data

– Mobile

• Innovation – The business cycle

– CAPEX, OPEX

• Business Intelligence – The BI Sweet Spot

6/4/2014 © 2013-2014 Michael Gendron 3

Page 4: Cloud computing, big data and mobile enhancing innovation through busine

Central Connecticut State University School of Business

Industry? Healthcare

Manufacturing Education

Insurance, Banking Or Other Financial Services Other

How would you categorize yourself?

Senior Staff (VP and Above) Middle Manager

Staff Consultant

6/4/2014 © 2013-2014 Michael Gendron 4

Page 5: Cloud computing, big data and mobile enhancing innovation through busine

Central Connecticut State University School of Business

Setting the Stage With Some Definitions

Cloud

Big Data Mobility

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Central Connecticut State University School of Business

THE CLOUD COMPUTING ECOSYSTEM

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Central Connecticut State University School of Business

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What Cloud Computing Isn’t

• The Cloud vs. Cloud Computing

– We use the term cloud to mean anything connected to the Internet…

– Cloud Computing requires Internet connection…But… • Not everything Internet connected is Cloud Computing

• E.G., Email might be offered on a cloud computing platform but may not be either.

• E.G., A USB hard drive accessible over the Internet is not cloud computing

THE CLOUD COMPUTING ECOSYSTEM

Page 8: Cloud computing, big data and mobile enhancing innovation through busine

Central Connecticut State University School of Business

What is Cloud Computing

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THE CLOUD COMPUTING ECOSYSTEM

Page 9: Cloud computing, big data and mobile enhancing innovation through busine

Central Connecticut State University School of Business

Best Practices

• Understand the difference between Cloud and Cloud Computing

• Have a firm grasp on how you are going to deploy a cloud computing environment: IaaS, PaaS, SaaS, Private, Public, Hybrid, Community

• Make sure your employee’s have the right skills • Know who the actors are in your cloud computing

project as they drive the project including cost and availability

6/4/2014 © 2013-2014 Michael Gendron 9

THE CLOUD COMPUTING ECOSYSTEM

Page 10: Cloud computing, big data and mobile enhancing innovation through busine

Central Connecticut State University School of Business

BIG DATA

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Page 11: Cloud computing, big data and mobile enhancing innovation through busine

Central Connecticut State University School of Business

• A phenomena not just large data bases

• Ubiquity of transactions: – Cloud Data Providers

– Mobile Computing

– Online transaction processing systems

– Anything else you can imagine

• High Volume, Velocity, Variety

• Technologies are associated with Big Data but is a phenomena: E.G. , Hadoop, SAS, NoSQL

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Big Data

Page 12: Cloud computing, big data and mobile enhancing innovation through busine

Central Connecticut State University School of Business

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Database

and DBMS, OLTP etc.

Data Model

Defines

Database

Data Aggregation Layer

Data Warehouse Created

by Aggregating Sources

Business

Intelligence

Business Analytics

Application

Cloud Data

Provider

Cloud Data

Provider

BIG DATA – BI IN THE CLOUD ERA

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Central Connecticut State University School of Business

6/4/2014 © 2013-2014 Michael Gendron 13

Data Stored

In House

Data Stored at

a Cloud Provider

BI

Applications

In House

BI

Applications

At Cloud

Provider

Decide Where Data

and BI Applications are

located

Any combination is possible

based on organizational

needs and objectives

BIG DATA – WHERE TO STORE DATA AND APPLICATIONS

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Central Connecticut State University School of Business

6/4/2014 © 2013-2014 Michael Gendron 14

BIG

DATA

BIG

DATA

BIG

DATA

BIG

DATABig

Data

Big

Data

Big

Data

Big

Data

High

Volume

High

Velocity

High

Variety

BIG DATA – HIGH VOLUME, VELOCITY, VARIETY

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Central Connecticut State University School of Business

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Predictive A

nalytic A

ccuracy

Vo

lum

e, V

elo

city

, Va

rie

ty o

f D

ata

Small

Large

Complexity of AnalyticsDescriptive Predictive

As the volume, velocity, and variety of

data increases so does the ability to create

more accurate and complex BI; small

amounts of data can be used for

descriptive analytics while larger amounts

of data can be suitable for more predictive

analytics

BIG DATA – IMPACT ON ANALYTICS

Page 16: Cloud computing, big data and mobile enhancing innovation through busine

Central Connecticut State University School of Business

Best Practices

• Know your data sources and what they add to the BI project

• Know the concept of Big Data as a phenomena rather than just technologies and understand what that means for your organization

• Determine the best location for your data and applications

• Know what BI you need and what data that requires (within and outside your organization)

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BIG DATA

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Central Connecticut State University School of Business

MOBILITY

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Central Connecticut State University School of Business

Definition of a Mobile Device

• Communicate over Mobile Networks

• Voice or Gesture Driven Interface

• Allow Apps

• Recognition of Geographic or Physical Context

• Computing Power

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Mobility

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Central Connecticut State University School of Business

Innovation In the Enterprise • Changes the way we do business

– Healthcare Delivery • Patient interactions

– Manufacturing • Supervisory Interactions

– Retail • Remote Cash Registers

– Warehouse • Inventory Control

– Employee and Consumer Interactions • Bank Account Access, Insurance Cards, Collect data (e.g., Customer

Sentiments), Self-Service Business Intelligence, etc.

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Mobility

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Central Connecticut State University School of Business

Best Practices

• Understand what a mobile device is – Smart phone, laptop, tablet….

• Know the limitations and advantages of mobile devices – Reach vs. Richness

– Type of interface, amount of data, security, etc.

• Coordinate desktop and mobile BI – Tethered and untethered

– Collection and dissemination

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Mobility

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Central Connecticut State University School of Business

INNOVATION

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Central Connecticut State University School of Business

How Cloud Computing, Big Data and Mobility Come Together

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Innovation

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Central Connecticut State University School of Business

Build VS Buy How CAPEX/OPEX is impacted

• The choices

– Build a BI infrastructure in house

– Buy a smaller in house infrastructure and use cloud providers for data, processing and self-service BI

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Innovation

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Central Connecticut State University School of Business

CAPEX vs. OPEX

• Capital Expense (CAPEX) – Purchase equipment and depreciate it over time

– Attempt to match costs of asset with income it generates

– Example: Purchase IT infrastructure

• Operating Expense (OPEX) – Buy Products/Services and Expense it during the

period used

– Example: Services of a Cloud Provider

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Innovation

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Central Connecticut State University School of Business

Scenario One: In House Infrastructure Budget YEAR

STARTUP

COSTS ONE TWO THREE FOUR FIVE

CAPITAL EXPENSES Initial In-House ICT 350,000 70,000 70,000 70,000 70,000 70,000

In-House Setup 65,000 13,000 13,000 13,000 13,000 13,000 Annual Capital Expenses (CAPEX) 43,000 43,000 43,000 43,000 43,000

Total 5 year CAPEX 215,000 OPERATING EXPENSES

In-House Personnel 160,000 168,000 176,400 185,220 194,481 In-House ICT Maintenance 59,500 62,475 65,599 68,879 72,323

Annual Operating Expenses (OPEX) 219,500 230,475 241,999 254,099 266,804 Total 5 Year OPEX 1,212,876

EXPENSES TO THE PROFIT AND LOSS STATEMENT

Annual Expenses 262,500 273,475 284,999 297,099 309,804 Total Five Year Expenses --> 1,427,876

Example – Build In house

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Innovation

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Central Connecticut State University School of Business

Example – Use Cloud Providers

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Scenario Two: External Cloud

YEAR

STARTUP COSTS ONE TWO THREE FOUR FIVE

CAPITAL EXPENSES

Initial In-House ICT 75,000 15,000 15,000 15,000 15,000 15,000

In-House Setup 15,000 3,000 3,000 3,000 3,000 3,000

Annual Capital Expenses (CAPEX) 18,000 18,000 18,000 18,000 18,000

Total 5 year CAPEX 90,000

OPERATING EXPENSES

In-House Personnel 75,000 78,750 82,688 86,822 91,163

In-House ICT Maintenance 5,400 5,670 5,954 6,251 6,564

Cloud Computing Service 210,000 220,500 231,525 243,101 255,256

Annual Operating Expenses (OPEX) 290,400 304,920 320,166 336,174 352,983

Total 5 Year OPEX 1,604,643

EXPENSES TO THE PROFIT AND LOSS STATEMENT

Annual Expenses 308,400 322,920 338,166 354,174 370,983

Total Five Year Expenses --> 1,694,643

Innovation

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Central Connecticut State University School of Business

CAPEX/OPEX Summary

6/4/2014 © 2013-2014 Michael Gendron 27

SUMMARY

Scenario One In

House

Scenario Two

External Cloud

Total 5 Year CAPEX 215,000 90,000

Total 5 Year OPEX 1,061,261 1,314,243

Total 5 Year Expenses to P&L 1,510,761 1,694,643

Year One Cash Needs 649,500 380,400

Five Year Expenses 1,510,761 1,694,643

Innovation

Page 28: Cloud computing, big data and mobile enhancing innovation through busine

Central Connecticut State University School of Business

Business/Innovation Cycle New

Innovation

Business Growth Causing

Increased Assets

Builds Small Infrastructure

Uses Cloud Providers

Greater Emphasis On OPEX

Moves to Hybrid

Infrastructure

Greater Emphasis On CAPEX

Change OPEX/CAPEX

Over Time

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Innovation

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Central Connecticut State University School of Business

Zynga’s Business Cycle and IT Deployment

6/4/2014 © 2013-2014 Michael Gendron 29

Hyb

rid

Clo

ud

P

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No

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Tra

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)

AW

S (P

eak

Load

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Level Out

Pu

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Clo

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M

ove

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per

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to A

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Initial Growth

Bu

ilt In

Ho

use

Infr

astr

uct

ure

Startup

Innovation

Page 30: Cloud computing, big data and mobile enhancing innovation through busine

Central Connecticut State University School of Business

PUTTING IT ALL TOGETHER

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Page 31: Cloud computing, big data and mobile enhancing innovation through busine

Central Connecticut State University School of Business

An Example: TripAdvisor

• Monetized via division that sells BI to the travel industry

• Mobile to connect users

• Cloud for processing and access

• Big Data to customer sentiments, reservation data from trips, social networking, etc.

6/4/2014 © 2013-2014 Michael Gendron 31

Putting It All Together

Page 32: Cloud computing, big data and mobile enhancing innovation through busine

Central Connecticut State University School of Business

How Implemented • Applications

– Wisdom of Friends – integration with Facebook

– City Guides – mobile application

– Maps – cloud geo-locater service

– Check Rates – cloud, big data

– TripWatch – email alerts

• All of these come together to create BI and the Sweet Spot for TripAdvisor

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Putting It All Together

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Central Connecticut State University School of Business

Trip Advisor and the BI Sweet Spot

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Customer and Industry Access Self Service BI

SAAS Services Consumers and Travel Industry

Customer Reviews Hotel and Other

Travel Data

Putting It All Together

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Central Connecticut State University School of Business

Contact • Personal Webpage: www.gendron.info • LinkedIn • Twitter: @BIAGendron • Email:

[email protected] and [email protected]

• Amazon Author Page – http://amazon.com/author/gendron

• Blog www.allanalytics.com • Current Book: Business Intelligence and the Cloud • I will be at @BigDataExpo in June 2014

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Page 35: Cloud computing, big data and mobile enhancing innovation through busine

Central Connecticut State University School of Business

• Raffle off two copies of my latest book

• Forming a workgroup

– Build business value in cloud and native applications

– Limited to 10 people and One year

– Develop best practices

– Please contact me if interested

6/4/2014 © 2013-2014 Michael Gendron 35