The Rise of Big Data and the Chief Data Officer (CDO)

The Rise of Big Data
and the Chief Data Officer
The “Minority Report©” Mall:
Step 1 on the Journey to Deliver Customer’s “REKAL©” Experience
in each Business “Matrix©”
1 Copyright © 2014 GTC Technology Consulting, Inc. All rights reserved.
GTC Technology Consulting, Inc.
Gerald T. Charles, Jr.
gcharles@GTCTechnology.com
August 2014

Agenda
What is Big Data and Why is it Important
Business relevancy and desired performance outcomes
The opportunity
The technical architecture behind it
Landmarks During the Journey
Influencers: Secure Mobility, Social media, and Sensor Networks
Crystal ball, newspaper, and/or black hole
Linking business strategy vs. creating tactical construction projects
Evolution: Achieving Insight, Differentiation, and Profits
Emergence of the Chief Data Officer
A Roadmap to Capitalize
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Why Is This So Cool Today?
(Knowledge is Power and Profit)
• “Minority Report©” mall is real and growing
Loyalty cards helping companies provide what you want,
when you want – maybe even before you know you want it
Social media trends, traffic, weather, web search trends,
and store sale data help companies manage their
inventory and personalize the services they deliver
Phones, watches, and other wearable sensors and devices
help track and manage our health, sports performance,
medical research, and in-store/venue experience
Part big brother, part advisor, part prophet
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According to
Analytics IQ’s
Business Imperative,
studies show that
organizations
competing on
analytics substantially
outperform their
peers by 220%
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Today’s Digital World Captures Data
Everywhere
Traditional data has been captured in enterprise data warehouses
 Relational Data (Tables and Transactions)
 Text Data (Web and traditional printed documents)
 Semi-structured and/or tagged Data (XML) that we search
Graphical and Image Data
 Parts of Social media (e.g. Instagram, Facebook, Pinterest)
 Video (e.g. YouTube)
Surveillance footage you can only scan once
 Streaming Data
Sensorial, data from embedded devices and applications
 Sensors in the road, clothes, medical devices, manufacturing, etc.
 GPS and mobile - Geo-tagging applications (e.g. Foursquare, Google Maps, etc.)
 Internet of Things
 Systems data (e.g. log, event, and error files)
Social
 Mining the wisdom of crowds (twitter, vine)
 Crowdsourcing5
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Social
Media
Website
Mobile & location
Email
Docs
Store
(online, bricks & mortar)
Transactions
User profiles
Historical
Sensors
iTunes and apps
Gesture technology
Internet/network

Data has Become the Latest IT Utility
Compute & Storage
 Commodization accelerating
Network & Communications
 Internet of Things (IoT) is at hand
 Cisco estimates by 2015 7.2B people will
have 25B devices connected
Data
 As of 2012, 2.5 Exabyte's (2.5×1018) of data
were created every day1
 Mobile devices and apps will generate
seven exabytes of data by 2015
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Gartner's Hype Cycles for
Emerging Technologies, 2011-2013
1 Big Data, Wikipedia

Big Data is Rising to the Top
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Gartner's Hype Cycles for
Emerging Technologies, 2011-2013
Gartner's Hype Cycles
for
Emerging Technologies,
2011-2013

… And Growing at an Exponential, Viral Rate
The volume of data is growing at a freighting rate.
Google’s executive chairman Eric Schmidt brings it
to a point: “From the dawn of civilization until
2003, humankind generated five exabytes of data.
Now we produce five exabytes every two days…and
the pace is accelerating.”
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Mashable.com

From Text-centric to Video-centric
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The Vectors of Big Data –
Volume, Variety, Velocity, and Veracity
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Volume
Variety
Velocity
Veracity
Mixture of raw, structured and unstructured data,
text, audio, video, web pages, logs, click-stream data,
search indexes, social media forums, email, and sensor data
Rate which data is generated, analyzed, and decided upon
Confidentiality, integrity, and availability of the data
Sheer amount of data

What to do (and not do)
with all this data?
Capture, Organize, and Manage it
 HADOOP Platform for handling all the various forms of data
 Aggregation and Statistics - Data warehouse and OLAP
 Indexing, Searching, and Querying
 Pattern matching (XML/RDF)
Discover Insight from the useful parts
 Data Mining, Collaborative Filtering, and Statistical Modeling
 Apply visualization tools to discover patterns
 According to IDC and EMC, only some 33 percent of 2020's 40,000EB (13,200EB) total might be
valuable if analyzed
Apply knowledge gained to drive goals, value, and profits
 Map to processes that drive performance and business differentiation
 Apply to decision making and strategic planning
 Integrate feedback (monitor, measure, and analyses) into ongoing innovation
and strategy processes
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$
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The Opportunity to
Accelerate Performance
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Data-driven decision-making
includes predictive analytics
(using historic and real-time data to make
future decisions), improving:
Revenue
 Companies using sentiment analysis of
Facebook and Twitter posts to determine
and predict sales volume and brand equity
 Supermarkets are combining their loyalty
card data with social media information to
detect and leverage changing buying
patterns
Profit (cost improvements)
 Manufacturers are monitoring minute
vibration data from their equipment,
which changes slightly as it wears down,
to predict the optimal time to replace or
maintain
 Transportation companies optimize their
routes and fuel usage based on sensor
data from vehicles, weather, online
destination queries, etc.
Quality
 Netflix mined its subscriber data to put the essential ingredients
together for its recent hit House of Cards
 Video analytics and sensor data of Baseball or Football games is used to
improve performance of players and teams. For example, you can now
buy a baseball with over 200 sensors in it that will give you detailed
feedback on how to improve your game
Customer/Citizen satisfaction
 Politicians are using social media analytics to determine where they
have to campaign the hardest to win the next election
 Artists like Lady Gaga are using data of our listening preferences and
sequences to determine the most popular playlist for her live gigs
Productivity/time savings
 GPS information on where our phone is and how fast it is moving is
now used to provide live traffic up-dates
 Google’s autocomplete and translate are based on comprehensive data
collection and real time analysis
Public service and safety
 The FBI is combining data from social media, CCTV cameras, phone calls
and texts to track down criminals and predict the next terrorist attack
The quality of your Information Management (IM) infrastructure
drives your strategy, performance, and outcomes

Agenda
The opportunity
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Shaping Influencers:
Secure Mobility, Social Media, and Sensor Networks
Secure mobility – The constant generation of real-time, personalized data
everywhere from everything drives services anywhere, anytime, on any screen
Fueled by the integration of Wi-Fi, Bluetooth, QR Codes, and NFC into mobile devices, the
benefits of mobile—location-aware (ubiquitous), real-time (immediate), and context-
aware (relevant) – marry context and personalization for real-time services and solutions
Social media verse – Tweets, FB updates, blogs (text, audio, and video), and our
digital footprints (e.g. logs from all devices and transactions) provide insight on
the crowd
Sensors and streaming data - exponential set of digital data sources to process,
analyze, and react to in real time. Data from vehicles, “wearable's”, buildings, etc.
to impact and dictate our decision making and experiences
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Creating a new perspective on context-aware computing - Gartner VP and Distinguished Analyst
Carl Claunch refers to this as the mix of location awareness, identity management,
the availability of a phone camera and microphone, and the user's social network,
all coming together to augment the computing experience.

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Creating the Crystal Ball
(vs. reading yesterday’s news)
In business, predictive models exploit patterns found in historical and
transactional data to identify risks and opportunities. Models capture
relationships among many factors to allow assessment of growth
potential (or risk) for various scenarios, guiding decision making
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1. Look for the patterns, look for things that cause
the “What if?” and “If only we could” questions
(it’s why the Data Visualization tool market is exploding)
2. Determine the predictive metrics — also known
as "leading indicators" — rather than just
historical metrics (aka "lagging indicators")
associated with the patterns
3. Build models that link these metrics to your
desired performance outcomes

Driving Strategy and Profits
(not local construction projects)
Data and research projects already going on in individual departments
So, its not about the individual projects to capture each data source, its
about collectively harnessing it all together in a context that drives
exponential value. What’s needed is:
Single source of truth for common overlapping data (cost and efficiency savings)
Attention, skills, expertise to capture new data sources of insight (mobile, social, and
sensorial)
Holistic view to capture (and find) opportunities that cut across data sources and
departments
Process of “patterns to predictive metrics to models driving desired outcomes”
Capturing larger short and long term revenues and profits due to opportunities
“bigger” than individual departments
Attention, Governance, and re-direction of investment for bigger payday17
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Agenda
The opportunity
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Who/How Do We Make This Happen?
A Champion is Needed to Lead it
1. Siloed information (and ownership) impairs enterprise level
resourcing, reporting, decision-making, and performance
2. Getting to the “single source of truth” (i.e. data quality)
3. Aggregated and analyzed information is required by certain business
functions, but not readily available. Knowledgeable decision-making
happen in the right “context” of information.
4. Business and IT functions, though measured and goaled differently
(speaking different languages), must be synchronized to drive top
level performance
5. The “necktie” to meet and manage regulatory compliance
6. Information-centric enterprises need a singular focus to analyze,
develop, and implement today’s enterprise corporate strategy
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The Chief Data Officer (CDO) Role
Knowledge harvesting for the enterprise from the
organization’s information assets – business,
technology, and control
Combine different data sources within the
organization with each other, and represent this as a
strategic business asset at board level
Deliver information strategy and architecture as a
shared service (e.g. BI function, IM SWAT teams)
Enabling/setting standards for regulatory compliance,
data policy, data security, privacy, and data retention
Operationalize a consistent data governance and
stewardship program, including data quality and IM
tools, standard data operating procedures, data
accountability policies
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The Chief Data Officer (CDO)
CDO isn’t an IT role, says Richard Wang, director
of the MIT Chief Data Officer Research Program.
Wang believes placing the CDO alongside the CIO
and CTO on the org chart is a best practice, one
that reduces almost inevitable conflict and
assures CEO attention to data projects. CDO is a
business role with strong technology skills.
 CIO’s top responsibility – making sure core
applications, critical systems, and IT
infrastructure are secure and safely operating –
leaves little time to ponder Big Data questions
Making enterprise data benefit the organization
as an asset while assuring the quality of
information being gathered and used
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CDO -
Architect & Oracle of Business
Business’ crystal ball to be guided by predictive
data and insights
Spend more time on answering “What ifs” and
“tomorrow they need…” then deliver those
outcomes
Help build tomorrow’s world today
No more Monday morning quarterbacking, rather
decision making and strategies center on
delivering the “ReKal©” experience – in each
business’ Matrix©22
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Today’s Business Organizations…
Push tons of personalized content, based on
user-provided preferences, TO their customers:
NFL Now – video clips, game day highlights
NBA All-Access, Fantasy, and newsletters
Marvel Unlimited (paid subscription) suite of apps
Government agencies: historical data and records
Are increasingly using social media information
(tweets, Facebook® posts, likes) to determine
audience/citizen sentiment
But still struggle to integrate channels – TV &
Movies, Web, Venues, Mobile Apps, VR and real-
life experiences -- let alone drive deeper,
engagement and loyalty
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Tomorrow’s
CDO-led Evolution
The CDO’s emergence is driving revenue, brand equity, and profits
to include:
Integration of omni-channels and data silos
Greater Insight – faster understanding of customer sentiment, trends, and
tomorrow’s desired services; increase responsiveness to optimize TV
ratings
Exponential increase in Customer interactivity -- Evolve from push
dominated to push and pull
Improving Player health, safety, and performance - sensor-best services
and apps
Increasing Differentiation – greater focus and delivery of core value
proposition
Improving Customer loyalty and deeper experiences – new data-based
services; from couch-gate to tailgate, improving game-day parking and
traffic, concession sales24
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Consider the CDO’s Impact
on a Big Data Strategy;
What if…
the NFL, NBA, and Marvel could increase and accelerate:
Their Digital Commerce
Use actionable customer insight for greater Customer
engagement, experience, and loyalty
Optimize their licensing merchandise
Maximize ticketing and licensing products (dynamic pricing)
Improve response and yields on promotions (localized on the
shelves, in the theatres, and at stadiums)
our public sector agencies could better predict surges and
demands for responding to:
Permits, applications, cases, etc.
Event and Emergency response
Political, Social, and economic trends
Healthcare response, patient outcomes
Transportation, including border/container management
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A New CDO’s Roadmap
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1. Clarify critical, strategic objectives, performance
measures, and business outcomes -- then identify what
data impacts them. Know the differentiation that’s
the heart of your business
2. Holistically organize your various data sources.
Governance of various data silos, architecture,
analytical tools, information storage, access, and
delivery
3. Structure and resource your organization to manage
 “Single Source of Truth” and secure data exchange
 Strategic business analyses (use cases) – where insight and
inspiration happens
 Communication, coordination, and support across existing/new
business processes
 Decision making
4. Coordinate across the organization to drive strategic
business interests; It’s not a greenfield situation, so
evolution must be managed

Acknowledgements
Big Data Spurs New Role: the Chief Data Officer, By David Coursey | Apr 7, 2014
The Role of the Chief Data Officer in Financial Services, Capgemini
Mobility and Big Data: Why They Need Each Other to Thrive, Scott Snyder, Xconomy
Gartner: Mobility, Big Data on the Rise; Cloud Not so Much, Dian Schaffhauser, 06/21/12
Its Time for a Big Data to improve Customer Experience, RazorFish
Big Data: The Mega-Trend That Will Impact All Our Lives, Bernard Marr, Aug 27, 2013
InfoSecurity Professional Magazine Issue 23, 2013 Vol 3
Analytics: Turning insights into action, Deloitte, November 2013
Big Data Analytics: Future architectures, Skills and Roadmaps for the CIO, Philip Carter, Sep 2011
Big Data, from Wikipedia
What Big Data Needs to Do to Grow Up, Mahesh S. Kumar, HBR Blog Network, June 6, 2014
Images from posts at The Celestial Convergence Blogspot, Ford’s Blueprint for Mobility, and SeedSpark Blog
How to Choose Your Social Business Intelligence Solution, Gianluigi Cuccureddu, April 15, 2013
Social Business Intelligence: Positioning a Strategic Lens on Opportunity, Dion Hinchcliffe, Aug 2011
The Big Deal About Big Data, Paul Paul Zikopoulos (IBM), June 2014
Dr. Dong Wang, Dept. of Computer Science and Engineering, iCeNSA, University of Notre Dame
Meet the Chief Data Officer, Brad Peters, The Economist Group, February, 2014
Post: Does data analytics need a c-suite champion?, Andrew Birmingham, May 2014
Steven Speilberg, (Director); (June 21, 2002). Minority Report. United States; 20th Century Fox, DreamWorks Studios
Larry and Andy Wachowski (Director); (September 21, 1999). The Matrix. United States: Warner Bros. Pictures.
Paul Verhoeven, (Director); (June 1, 1990). Total Recall. United States; TriStar Pictures, Inc.
Len Wiseman, (Director); (August 3, 2012). Total Recall. United States; Columbia Pictures27
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The Rise of Big Data and the Chief Data Officer (CDO)

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