Presented at InnOTe

1. 4/18/2013
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The Future of Advance Analytics
David Smith
Chief Executive Officer, HBMG Inc.
dsmith@hbmginc.com
Room: Room: 102B
Volume, variety, and velocity are changing us in our companies, government
agencies and at home. How do BI, Social/Business media, mobility, Devices and Big
Data drive business decisions? The success is driven by the use of advance
analytics. Business analytics facilitates realization of business objectives through
reporting of data to analyze trends, creating predictive models for forecasting and
optimizing business processes for enhanced performance. This is important not only
in business but the military and government as well.
This presentation will look at the current and future trends in analytics and how they
will impact each of us. Special emphasis will be given to the new trend of embedded
analytics. As the world moves faster toward real-time the analytics must move as
well. Attendees will leave the session with a understanding of the future directions of
advance analytics.
The Future of
Advance
AnalyticsAnalytics
David Smith
CEO HBMGInc.
dsmith@HBMGINC.com

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Definition for Advanced Analytics
Analysis is the examination process itself where
analytics is the supporting technology and
associated tools. BI is quite synonymous to
analytics in IT context. Advanced Analytics,
Business Analytics, Data Analytics, Analytics
Software, Analytics Technology are almost
always marketing pleonasms (redundantalways marketing pleonasms (redundant
expressions) and can be safely substituted by
just ‘analytics’
Definition for Advanced Analytics
Analysis is a pretty old, well understood term
d ti ll “b ki d ”and essentially means “breaking down” or
“decomposition”. More accurately –the
process of decomposing complex entity into
simpler components for easier
comprehension.

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Definition for Advanced Analytics
Advanced analytics provides algorithms for complex analysis of
either structured or unstructured data. It includes
sophisticated statistical models, machine learning, neural
networks, text analytics, and other advanced data mining
techniques. Among its many use cases, it can be deployed to
find patterns in data, prediction, optimization, forecasting,
and for complex event processing/analysis. Examples include
predicting churn, identifying fraud, market basket analysis, or
understanding website behavior Advanced analytics does notunderstanding website behavior. Advanced analytics does not
include database query and reporting and OLAP cubes.
America gets more than half its economic
growth from industries that barely existed
a decade ago—such is the power of
innovation, especially in the information
and biotechnology industries.
—The Economist
Copyright, 2011 © HBMG, Inc.

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Business Problem
More than half of business and IT executives, 56
percent, report they feel overwhelmed by the
amount of data their company manages.
Many report they are often delayed in making
important decisions as a result of too much
information. Surprisingly, 62 percent of C‐level
respondents – whose time is considered the respondents whose time is considered the
most valuable in most organizations – report
being frequently interrupted by irrelevant
incoming data.

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Why?
• Technological innovation is now the most
important driver for competitive success
– Many firms earn over one‐third of sales on
products developed within last five years
• Product life cycles ( time between product
introduction to market and its withdrawal)
Copyright, 2011 © HBMG, Inc.
– Software 4‐12 months
– Computer hardware 12‐24 months
– Large home appliances 18‐36 months
Business, Knowledge, and Innovation Landscape
• Typically 80% of the key knowledge (and value) is
held by 20% of the people – we need to get it to theheld by 20% of the people we need to get it to the
right people
• Only 20% of the knowledge in an organization is
typically used (the rest being undiscovered or under‐
utilized)
80 90% f th d t d i t d ill b• 80‐90% of the products and services today will be
obsolete in 10 years – companies need to innovate &
invent faster
Copyright 2012@ HBMG Inc.

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Tapping into the Data
• Data Storage
• Reporting
• Analytics
Utilized data
• Analytics
• Advanced
Analytics
– Computing with
big datasets is a
Unutilized data
that can be
il bl t
g
fundamentally
different challenge
than doing “big
compute” over a
small dataset
available to
business
Innovation:
‘The real voyage of discovery consists
not in seeing new lands,
but in seeing with new eyes’
(Source: Marcel Proust)
‘Innovation =
creative idea and
implementation’
(Source: Glossary of Electronics)
‘Innovation: change that
‘A new method, idea,
product, etc’
(Source: Oxford English
Dictionary)
creates a new dimension of
performance’
(Source: Peter Drucker)
‘An innovation to be effective
has to be simple and it has
to be focused’
(Source: Peter Drucker)
‘Value innovators look for
what customers value in
common’
(Source: Kim & Mauborgne)
‘Innovation is the process by which new products or
methods of production are introduced, including all
the steps from the inventor’s idea to bringing the
new item to market’
(Source: Baumol, Economics: Principles & Policy)
(Source: Peter Drucker)
‘Firms need to manage steady state
innovation and radical change because
continuous improvement is no longer
enough’
(Source: Tom Peters)

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“Big Data” and it’s close relatives “Cloud
Computing”, “Social Media” and
"Mobile"
are the new frontier of innovation.
Driven by Advance Analytics
Big Data and It’s Brothers
VolumeVolume
Variety
Velocity
………..

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Volume
Volume is increasing at incredible rates.
h l h h dWith more people using high speed
internet connections than ever, plus
these people becoming more proficient
at creating content and just more
people in general contributing
information are combined forces thatinformation are combined forces that
are causing this tremendous increase in
Volume.
Variety
Next in breaking down Big Data into easily digestible bite‐
size chunks is the concept of Variety. Take your personal
experience and think about how much information youexperience and think about how much information you
create and contribute in your daily routine. Your
voicemails, your e‐mails, your file shares, your TV
viewing habits, your Facebook updates, your LinkedIn
activity, your credit card transactions, etc.
Whether you consciously think about it or not the VarietyWhether you consciously think about it or not the Variety
of information you personally create on a daily basis
which is being collected and analyzed is simply
overwhelming.

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Velocity
The speed at which data enters organizations
these days is absolutely amazing. With mega
internet bandwidth nearly being common
place anymore in conjunction with the
proliferation of mobile devices, this simply
gives people more opportunity than ever to
contribute content to storage systems. contribute content to storage systems.
Worldwide digital content will
double in 18 months, and
every 18 months thereafter.
VELOCITY
IDC
CRM Data
GPS
Demand
Speed
Velocity
Opportunities
Customer
Inventory
Emails
Tweets
Planning
Mobile
InstantMessages
VOLUME VARIETY
Transactions
ServiceCalls
Sales Orders
ThingsIn 2005, humankind
created 150 exabytes of
information. In 2011,
over 1,200 exabytes was
created.
VOLUME
80% of enterprise data
will be unstructured,
spanning traditional and
non traditional sources.
Gartner
The Economist

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But I Believe there are Four V4
• Volume：Gigabyte(109), Terabyte(1012),
Petabyte(1015), Exabyte(1018), Zettabytes(1021)
• Variety: Structured,semi‐structured, unstructured;
Text, image, audio, video, record
• Velocity(Dynamic, sometimes time‐varying)
• BUT needs to add and create Value!• BUT needs to add and create Value!

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Trends driving data management
– The volume of data has never been greater and is
growing exponentially
– The value of data has never been better understood– The value of data has never been better understood
– The capabilities for processing data have never been
better
• Higher processor performance and density are enabling
advanced processing on commodity hardware
• Software enhancements designed to make best use of
i f d l bl hit tprocessing performance and scalable architecture
• Advanced and in‐database analytics bring processing to the
data, reducing latency and improving efficiency
– The data deluge problem is also a big data opportunity
21
Copyright, 2011 © HBMG, Inc.From http://geekandpoke.typepad.com

12. 4/18/2013
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Next Generation
• Cloud Computing (e.g. “Blue Cloud”)
– The “network becomes the computer”
D b d i ??????– Dumb devices ??????
• Pervasive Computing
– Monitoring and tracking almost anything
– The Internet is Free
• Continuous Services
• The Cloud + Pervasive Computing
– Smart buildingsSmart buildings
– Sensor nets
– “Invisible computing” or “ubiquitous computing”
– Semantic Interoperability
– Ad hoc networking
Copyright 2012@ HBMG Inc.
Advance Analytics as a strategic asset
“The future belongs to companies and people
that turn data into products.”
Mike Loukides, O’Reilly
24

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Advance Analytics as a strategic asset
“85% of eBay’s analytic workload is new and
unknown. We are architected for the unknown.”
Oliver Ratzesberger, eBay
• Data exploration – data as the new oil
 The exploration for data, rather than the exploration of data
 Uncovering pockets of untapped data
 Processing the whole data set, without sampling
 eBay’s Singularity platform combines transactional data with
behavioral data, enabled identification of top sellers, driving
increased revenue from those sellers
25
Advance Analytics as a strategic asset
“Groupon will not be the first or last organization to
compete and win on the power of data It’s happeningcompete and win on the power of data. It s happening
everywhere.”
Reid Hoffman and James Slavet
Greylock Partners
Data harnessing – data as renewable energy
H i t ll i d t t Harnessing naturally occurring data streams
 Like harnessing raw energy to be converted into usable energy
 Conversion of raw data into usable data
26

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Facebook
27
BIG DATA
REAL TIME
PREDICTIVE
ENABLED BYENABLED BY
ADVANCE ANALYTICS

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As the world gets smarter, infrastructure
demands will grow
Smart
traffic
systems
Smart
energy
grids
Smart
healthcare
Smart
food
systems
Intelligent oil
field
technologies
Smart retail
Smart water
management
Smart
regions
Smart
weather
Smart
countries
Smart
supply
chains
Smart
cities
Data
Desktop

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Knowledge
Copyright 2012@ HBMG Inc.

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The Nature of Communications
Has Been Changing...
People to
Things
People to
People
Things to
Things
People to
Things
People to
People
Things to
Things
TOL
L
TOL
L
TOL
L
TOL
L
ThingsPeople ThingsThingsPeople Things
Copyright, 2011 © HBMG, Inc.
15.62 Gallons
27.33 Dollars
Thank You!
15.62 Gallons
27.33 Dollars
Thank You!
15.62 Gallons
27.33 Dollars
Thank You!
Mainframe/Terminal
Client Server
Ubiquitous
COSTS
Mainframe
Mini/Terminal
Server/PC
ASP/Appliance
USAGE
Distribution of Computing Power Virtualization Ubiquitous
Improved Access/Convenience
Improved Ease of Use
Large Organizations + Small Organizations + Departments + BYOD Entrepreneurs
Middle Class (PCs) + General Population

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Digital Video Adapters
Satellite Radio
Receivers
Digital Cameras
PDAs
Wireless CamerasWireless TV
Monitors
Digital Music
Adapters
Networked Storage
Centers
Game Consoles
Smart Displays
Smart Phones
Laptop PCs
Desktop PCs
Wireless Gaming
Adapters
Movies-on-Demand
Receivers
“Fourth Generation”
Set-top Boxes
MP3 PlayersDigital Media Receivers Personal Video
Recorders
Networked DVD Player Mobile Gaming
Devices
802.11 Speakers
Copyright, 2012 © HBMG, Inc.
The Global Grid
Copyright 2012@ HBMG Inc.

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To Every Sensor is a Server
Phone -PDA
Processor
Data Storage
Communications
Rich variety of
sensors
Smart Dust
Microphone
Microstorage
(Areal density 100x’s CD)
Copyright, 2011 © HBMG, Inc.
Embedded
Biofluidics Chip
Robot
3,500
4,000
• Mobile
Growth at the Edge of the Network
1,000
1,500
2,000
2,500
3,000
Petabytes/DayGlobal
Mobile
• Device to Device
• Sensors
• Entertainment
• Smart Home
• Distributed Industrial
• Autos/Trucks
• Smart Toys
Converged
Content
0
500
2003 2004 2005 2006 2007 2008 2009 2010 2011
Year
2012
Traditional
Computation
Copyright 2012@ HBMG Inc.

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DOD ExampleDOD Example
 Counterinsurgency operations are complex  increased emphasis
on:
 Information and analysis at lowest levels
 Shortened decision making time-scales
Operation Trends
Source: TTI Vanguard Conference - Psydex
g
 Wider array of information sources
 Continued growth in volume of data, especially informal information
with limited structure  must transform disparate info to knowledge
 Processing power and storage capacity increasing faster than
communications capacity  must smartly position data and services
within networks
 Increased use of commercial cellular networks  hybrid networks Increased use of commercial cellular networks  hybrid networks
that exploit and interoperate with commercial wireless comms is key
 Enhancing coalition decision making depends on secure
communications and information networks  must address end-to-
end problem of data-to-decision (coalition)

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“Recce” P-38“Recce” P-38
RF-101 Voodoo
Info in War Revolution
Technology—Information—Organization
B-17 Spotter
Corps
0-2 Bird Dog
0-2 Bird DogB-52
75 Days75 Days
14 Days14 Days
<10 Minutes<10 Minutes
N b f W N b f S
RS
I
R
I
S ISR?
41
Evolution of Technology, Information, and Culture Enabled Move from Evolution of Technology, Information, and Culture Enabled Move from
Segregation of Ops and Intel to Integration of Ops and Intel…Segregation of Ops and Intel to Integration of Ops and Intel…
Number of Weapons
Required to Target
Number of Sensors
Required to Target
19431943 20092009
National
Strategic
StrategicStrategic
OperationalOperationalOperational
AIRAIR
SPACSPAC
CYBECYBE
StrategicStrategic
OperationalOperational
StrategicStrategic
OperationalOperational
21st Century Challenges:
Precision and Information Synergy
Tactical
OperationalOperational
TacticalTactical
Tactical
DESERT
STORM
1991 & Prior
1999
ALLIED
FORCE
2001
ENDURING
FREEDOM
2009
AF/PAK & Iraq
TODAY
INFO AGEINFO AGE
WARFAREWARFARE
TOMORROWTOMORROW
RR
CECE
ERER
TacticalTactical
pp
TacticalTactical
Ops …
+ Intel
I + S&R GLOBAL
INTEGRATED
ISRSegregated
Intel & Ops
NTI
+ Intel INTEGRATED
ISR
Intel & Ops
Kandahar
Runway
Pod Recce
Real‐Time
Fusion
OPS
INTEL
Multi‐Domain
Fusion

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More CollectorsMore Collectors
Better SensorsBetter Sensors
Dimensions of ISR…
“More of Everything”
More DataMore Data
•• More StorageMore Storage
•• More CommsMore Comms
•• More ToolsMore Tools
•• More AnalystsMore Analysts
•• More LinguistsMore Linguists
Better Intel
…All on an Operationally Responsive Timeline…All on an Operationally Responsive Timeline
Sensor Data Volume
How do we handle all this data?How do we handle all this data?
“Rebalancing Collection & PED may be Necessary”“Rebalancing Collection & PED may be Necessary”

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Persistent Surveillance Data Rates
General Norton A. Schwartz
Air Force’s chief of staff
“If i id f l h“If automation can provide a cue for our people that
would make better use of their time, that would help us
significantly,” NY Times.
Lieutenant General David Deptula
Former Deputy Chief of Staff for ISR, Headquarters, US Air p y f f ff f q
Force
“We’re going to find ourselves in the not too distant future
swimming in sensors and drowning in data”

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Advance Analytics
• Advanced Analytics and Big Data are two of the
most active areas of innovation in the Tech
sector
• legacy infrastructures and government policies are
increasingly at odds with the realities of the analytic
landscape
• Certain forms of analysis is no longer possible within
an encrypted environment. Rules that require data
to be encrypted, both while in transit and at rest,
also introduce performance penalties that make it
difficult if not impossible to process large datasets in
an acceptable timeframe
Today's Cycle
Where is Real Time?

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Advance Analytics
• The time to use the output is increasingly getting
shorter – Real Time is becoming very common
Li it d il bl h d f i• Limited available human resources, and performance is
often unreliable due to human fatigue and distraction.
Therefore, automated real‐time sensor processing
techniques are required to reliably detect and
discriminate targets of interest
• Limited automated processing and tagging tools
• – Still NOT enough
Advance Analytics
• The time to use the output is increasingly getting shorter – Real
Time is becoming very common
• Limited available human resources, and performance is often p
unreliable due to human fatigue and distraction. Therefore,
automated real‐time sensor processing techniques are required to
reliably detect and discriminate targets of interest – Still NOT
enough
• Need to move to the
sensor/collector
• Needs to be embedded in the
the sensor

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Autonomous Systems
Agents coordinate
and negotiate to achieve
common goals
Agents dynamically adapt
to and learn about
their environment
Adaptive
Autonomous Mobile Interoperate
Cooperative
Social
PersonalityIntelligent
Agents
Information
Agents
HBMG Inc. Copyright 2012
Agents are goal directed
and act on their
own performing
tasks on your behalf
Agents move
to where they
are needed
Agents interoperate
with humans, other,
legacy systems, and
information sources
Numbers
• How many data in the world?
– 800 Terabytes, 2000
– 160 Exabytes, 2006
– 500 Exabytes(Internet), 2009
– 2.7 Zettabytes, 2012
– 35 Zettabytes by 2020
• How many data generated ONE day?
– 7 TB, Twitter
– 10 TB, Facebook
Big data: The next frontier for innovation, competition, and productivity
McKinsey Global Institute 2011

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1 illi1million
transactions during this presentation
If You Liked ____, You’ll Love ___ !

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1billi1billion
clicks during this presentation

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Gartner Hype Cycle 2012

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2012 Business Intelligence, Analytics and Information
Management Survey from InformationWeek Reports
A few insights from the report:
•58% of those surveyed are “very interested” in advanced analyticsy y y
•Advanced analytics is the No. 1 leading-edge technology
•Cloud analytics systems are hot because they are easier on the
pocketbook; yet 63% of users have privacy concerns
•Data pros just can’t get good data – data quality still ranks as the top
barrier to adopting BI products throughout the company
•25% of those surveyed are mobilizing their data analytics with
dashboards and data visualizations
40% f d t t li t t b th bi d t•40% of data pros are struggling to stay above the big data wave
Conclusion
 Data is one the major factors driving infrastructure computing
 The growing volume of data is a problem, but it is also an opportunity
 Don’t worry about ‘big data,’ worry about your datay g , y y
 Take a Total Data approach to data management
• Think pragmatically about data storage and analysis
• Attempt to capture and analyze any data that might be relevant,
regardless of where it resides
 ‘Datastructure’ will become increasingly valuable, not only as a source of
data but also as a source of intelligence
 The rise of the ‘data cloud’ and the PaaS data layer will encourage a
more flexible approach to data management and analytics
 The companies that win will be those that think about data as a strategic
asset and implement the technology to monetize it

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Conclusion
The World is moving to Real Time
Advanced Analytics is the Keyy y
Advanced Analytics Must be embedded in the
collectors and sensors
• Think about where the data comes from
• Attempt to capture and analyze any data that
might be relevant, regardless of where it resides
• Realize collaboration is the key in Advance
Analytics just as it is in Business
If we don’t change ourIf we don t change our
direction, we’ll end up exactly
where we are headed.
—Ancient Chinese Proverb

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In Parting: Be Paranoid
•“Sooner or later, something
fundamental in your business world
•“Sooner or later, something
fundamental in your business worldfundamental in your business world
will change.”
• Andrew S. Grove, Founder, Intel
“Only the Paranoid Survive”
fundamental in your business world
will change.”
• Andrew S. Grove, Founder, Intel
“Only the Paranoid Survive”Only the Paranoid SurviveOnly the Paranoid Survive
Copyright @2008 HBMG Inc.