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4/25/2017
1
The New Convergence of Data; the
Next Strategic Business Advantage
David Smith
The growth of data has accelerated beyond even the fastest forecast of a few years ago. The new definition of
convergence is very different from even a decade ago. The new trends of Big Data, Data Science, Cloud, A I,
Mobilityand IoT are changing how organizations are using data. It is now a critical business asset. New
business processes will revolve around the data and it will soon become even more intensive through massive
streaming data coming from ubiquitous sensors in the Internet of Things. Variety, not volume or velocitywill
drive the investments. During this session you will see how the data has become a strategic business advantage
and its value will only increase in the next decade
David Smith
President
dsmith@socialcare.com
linkedin.com/in/davidsmithaustin
The New
Convergence of
Data; the Next
Strategic Business
Advantage
4/25/2017
2
Predictions of Lord Kelvin,
president of the Royal
Society, 1890-95
• "Radio has no future"
• "Heavier than air flying machines are
impossible"
• "X rays will prove to be a hoax”
Why bother with the future?
"If you think that you can run an
organization in the next 10 years as
you've run it in the past 10 years you're
out of your mind.“
CEO,
Coca Cola
4/25/2017
3
The Age of Data
In the last two years we have generated more data than in
the history of mankind
Data is expected to double in size every two years
through 2020, exceeding 40 zettabytes (40 trillion
gigabytes)
2020
2012 - 2014
The Beginning –
2011 The Economist:
digital information increases10
times/5 years!
2016 - 2017
Forecast of Data Growth
zettabytes (ZB) – 1 of which accounts for 1 billion terabytes (TB)
4/25/2017
4
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 most valuable in most
organizations – report being frequently
interrupted by irrelevant incoming data.
4/25/2017
5
Entering the Age of Data
Data is THE central business asset:
– “Data are an organization’s sole, non-depletable, non-
degrading, durable asset. Engineered right, data’s value
increases over time because the added dimensions of
time, geography, and precision.” (Peter Aitken)
Data generation has changed forever
– Instrumentation of All businesses, people, machines
Data is born digitally and flows constantly
– “All things are flowing..” (Heraclitus, 500 BC)
4/25/2017
6
The past fifteen years have seen extensive
investments in business infrastructure, which
have improved the ability to collect data
throughout the enterprise.
Virtually every aspect of business is now open to
data collection and often even instrumented for
data collection: operations, manufacturing,
supply-chain management, customer behavior,
marketing campaign performance, workflow
procedures, and so on.
At the same time, information is now widely
available on external events such as market
trends, industry news, and competitor’s
movements.
This broad availability of data has led to increasing
interest in methods for extracting useful
information and knowledge from data-the realm
of data science.
11
DATA
4/25/2017
7
Types of Data
4/25/2017
8
Today most data is retrospective,
there is a need for real-time and
predictive
Retrospective
Real-time
Predictive
Today's Cycle
Where is Real Time?
4/25/2017
9
Volume
Variety
Velocity
………..
Volume
Volume is increasing at incredible
rates. With more people using
high speed internet connections
than ever, plus the growth of IoT
and always on devices these are
causing this tremendous increase
in Volume.
4/25/2017
10
Variety
Next in breaking down Data into easily digestible
bite-size chunks is the concept of Variety. Take
your personal experience 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
Variety of information you personally create on a
daily basis which is being collected and analyzed
is simply overwhelming.
Variety
•FB generates 10TB daily
•Twitter generates 7TB of data
Daily
•IBM claims 90% of today’s
stored data was generated
in just the last two years.
4/25/2017
11
Variety
Big Data isn't just numbers, dates, and strings.
Big Data is also geospatial data, 3D data,
audio and video, and unstructured text,
including log files and social media.
Traditional database systems were designed to
address smaller volumes of structured data,
fewer updates or a predictable, consistent
data structure.
Streaming data and real-time analysis includes
different types of data
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.
4/25/2017
12
Velocity
• Clickstreams and ad impressions capture user
behavior at millions of events per second
• High-frequency stock trading algorithms reflect
market changes within microseconds
• Machine to machine processes exchange data
between billions of devices
• Infrastructure and sensors generate massive log
data in real-time
• On-line gaming systems support millions of
concurrent users, each producing multiple inputs
per second.
But I Believe These are the Real Four
4/25/2017
13
The Structure of Data
 Structured
• Most traditional data
sources
 Semi-structured
• Many sources of big data
 Unstructured
• Video data, audio data
25
Historical Development of Database
Technology
Early Database Applications: The Hierarchical and
Network Models were introduced in mid 1960’s
and dominated during the seventies. A bulk of
the worldwide database processing still occurs
using these models.
Relational Model based Systems: The model that
was originally introduced in 1970 was heavily
researched and experimented with in IBM and the
universities. Relational DBMS Products emerged
in the 1980’s.
4/25/2017
14
Historical Development of Database
Technology
Object-oriented applications: OODBMSs were
introduced in late 1980’s and early 1990’s to
cater to the need of complex data
processing in CAD and other applications.
Data on the Web and E-commerce
Applications: Web contains data in HTML
(Hypertext markup language) with links
among pages. This has given rise to a new
set of applications and E-commerce is using
new standards like XML (eXtended Markup
Language).
Extending Database Capabilities
New functionality is being added to DBMSs in
the following areas:
– Scientific Applications
– Image Storage and Management
– Audio and Video data management
– Data Mining
– Spatial data management
– Time Series and Historical Data Management
– IoT
– Streaming
The above gives rise to new research and development in
incorporating new data types, complex data structures, new
operations and storage and indexing schemes in database
systems.
4/25/2017
15
Top10 Time Series Databases
• DalmatinerDB
• InfluxDB
• Prometheus
• Riak TS
• OpenTSDB
• KairosDB
• Elasticsearch
• Druid
• Blueflood
• Graphite (Whisper)
4/25/2017
16
The Intelligence is in the Connections
Connections between people
ConnectionsbetweenInformation
Email
Social Networking
Groupware
Javascrip
t Weblogs
Databases
File Systems
HTTP
Keyword Search
USENET
Wikis
Websites
Directory Portals
2010 -
2020
Web 1.0
2000 - 2010
1990 - 2000
PC Era
1980 - 1990
RSS
Widgets
PC’s
2020 - 2030
Office 2.0
XML
RDF
SPARQLAJAX
FTP IRC
SOA
P
Mashups
File Servers
Social Media Sharing
Lightweight Collaboration
ATOM
Web 3.0
Web 4.0
Semantic Search
Semantic Databases
Distributed Search
Intelligent personal agents
Java
SaaS
Web 2.0Flash
OWL
HTML
SGML
SQL
Gopher
P2P
The Web
The PC
Windows
MacOS
SWRL
OpenID
BBS
MMO’s
VR
Semantic Web
Intelligent Web
The Internet
Social Web
Web OS
Source: Gartner, Cisco, DSmith
Big Challenge
24/7 Streaming Data
It seems that everything in 2017 will have a
sensor that sends information back to the
mothership.
4/25/2017
17
The Ubiquity of Data Opportunities
With vast amounts of data now available, companies in
almost every industry are focused on exploiting data for
competitive advantage.
In the past, firms could employ teams of statisticians,
modelers, and analysts to explore datasets manually, but
the volume and variety of data have far outstripped the
capacity of manual analysis.
At the same time, computers have become far more
powerful, networking has become ubiquitous, and
algorithms have been developed that can connect
datasets to enable broader and deeper analyses than
previously possible.
The convergence of these phenomena has given rise to the
increasing widespread business application of data
science principles and data mining techniques.
33
Data Science 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 34
4/25/2017
18
Data as a strategic asset
“Groupon will not be the first or last organization
to compete and win on the power of data. It’s
happening everywhere.”
Reid Hoffman and James Slavet
Greylock Partners
Data harnessing – data as renewable energy
 Harnessing naturally occurring data streams
 Like harnessing raw energy to be converted into usable
energy
 Conversion of raw data into usable data
35
Emergence of a Fourth Research
Paradigm: Data Science
Thousand years ago –
– Experimental Science
Description of natural phenomena
Last few hundred years –
– Theoretical Science
Newton’s Laws, Maxwell’s Equations…
Last few decades –
– Computational Science
Simulation of complex phenomena
Today –
– Data-Intensive Science
Scientists overwhelmed with data!
4/25/2017
19
Key to Creating Artificial General Intelligence:
Increasing Computational Power
NNow =
• Beating a
mouse brain
• About a
thousandth of
a human
4/25/2017
20
Information and Communication
Trends
• Seamless Interoperability Between
Heterogeneous Networks
• Mobility for All – Devices for All Things
• User Centered Content-Based Information
Access
• Agents Take Over Routine Work
• “E”- Processes for Business and Private Life
• Human Computer Interaction is Turning Into
Human Computer Cooperation
• Human is not part of most computer and data
interaction
The “Fat Pipe”
4/25/2017
21
What is direction of DATA
Walmart handles more than 1 million customer
transactions every hour.
• Facebook handles 40 billion photos from its
user base.
• Decoding the human genome originally took
10years to process; now it can be achieved
in one week.
“The market for enterprise AI systems will increase from $202.5 million
in 2015 to $11.1 billion by 2024.”
- Tractica
4/25/2017
22
Internet of Things:
The Next Frontier
Data available from “Internet of
Things”
4/25/2017
23
IoT is generating massive volumes of structured and
unstructured data, and an increasing share of this data is
being deployed on cloud services. The data is often
heterogeneous and lives across multiple relational and
non-relational systems.
When these smart devices are connected to intelligent
applications such as Siri, Alexa ,Cortana or Google Home,
the possibilities become endless. Conversational AI will
enable high-level conversations with these intelligent
applications These bots, per Microsoft CEO Satya Nadella,
will be the next apps. 2017 will see the convergence of
these intelligent applications with many IoT devices.
As the world gets smarter,
infrastructure demands will grow
Smart
traffic
systems
Smart water
management
Smart
energy
grids
Smart
healthcare
Smart
food
systems
Smart oil
field
technologies
Smart
regions
Smart
weather
Smart
countries
Smart
supply
chains
Smart
cities
Smart retail
4/25/2017
24
Domestic Robots
4/25/2017
25
4/25/2017
26
Will technological breakthroughs be developed in time to boost economic productivity and
solve the problems caused by a growing world population, rapid urbanization, and climate
change?
Game Changer - Impact of New Technologies
• The Internet of Things
• Not just Big Data, but a zettaflood
• Much D to D
• Wisdom of the Data Science
• The next 'Net
• Move from physical to virtual
• The world gets Bio
• Regenerative Medicine
Conclusion
The Age of Data is here
Data is the central business asset
Data generation has changed forever
• The World is moving to Real Time
• Data Science is the Key
Your legacy analytic software WILL fail in the Age of
Data
Crisis of software that scales to meet demand
Streaming data changes the concept of data
Think about where the data comes from
Attempt to capture and analyze any data that might be
relevant, regardless of where it resides
Data Science is changing how data is:
– Collected, discovered, analyzed, used, acted upon …
4/25/2017
27
In Parting: Be Paranoid
“Sooner or later, something
fundamental in your business
world will change.”
 Andrew S. Grove, Founder, Intel
“Only the Paranoid Survive”
Thank You
David Smith
dsmith@socialcare.com

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The New Convergence of Data; The Next Strategic Business Advantage

  • 1. 4/25/2017 1 The New Convergence of Data; the Next Strategic Business Advantage David Smith The growth of data has accelerated beyond even the fastest forecast of a few years ago. The new definition of convergence is very different from even a decade ago. The new trends of Big Data, Data Science, Cloud, A I, Mobilityand IoT are changing how organizations are using data. It is now a critical business asset. New business processes will revolve around the data and it will soon become even more intensive through massive streaming data coming from ubiquitous sensors in the Internet of Things. Variety, not volume or velocitywill drive the investments. During this session you will see how the data has become a strategic business advantage and its value will only increase in the next decade David Smith President dsmith@socialcare.com linkedin.com/in/davidsmithaustin The New Convergence of Data; the Next Strategic Business Advantage
  • 2. 4/25/2017 2 Predictions of Lord Kelvin, president of the Royal Society, 1890-95 • "Radio has no future" • "Heavier than air flying machines are impossible" • "X rays will prove to be a hoax” Why bother with the future? "If you think that you can run an organization in the next 10 years as you've run it in the past 10 years you're out of your mind.“ CEO, Coca Cola
  • 3. 4/25/2017 3 The Age of Data In the last two years we have generated more data than in the history of mankind Data is expected to double in size every two years through 2020, exceeding 40 zettabytes (40 trillion gigabytes) 2020 2012 - 2014 The Beginning – 2011 The Economist: digital information increases10 times/5 years! 2016 - 2017 Forecast of Data Growth zettabytes (ZB) – 1 of which accounts for 1 billion terabytes (TB)
  • 4. 4/25/2017 4 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 most valuable in most organizations – report being frequently interrupted by irrelevant incoming data.
  • 5. 4/25/2017 5 Entering the Age of Data Data is THE central business asset: – “Data are an organization’s sole, non-depletable, non- degrading, durable asset. Engineered right, data’s value increases over time because the added dimensions of time, geography, and precision.” (Peter Aitken) Data generation has changed forever – Instrumentation of All businesses, people, machines Data is born digitally and flows constantly – “All things are flowing..” (Heraclitus, 500 BC)
  • 6. 4/25/2017 6 The past fifteen years have seen extensive investments in business infrastructure, which have improved the ability to collect data throughout the enterprise. Virtually every aspect of business is now open to data collection and often even instrumented for data collection: operations, manufacturing, supply-chain management, customer behavior, marketing campaign performance, workflow procedures, and so on. At the same time, information is now widely available on external events such as market trends, industry news, and competitor’s movements. This broad availability of data has led to increasing interest in methods for extracting useful information and knowledge from data-the realm of data science. 11 DATA
  • 8. 4/25/2017 8 Today most data is retrospective, there is a need for real-time and predictive Retrospective Real-time Predictive Today's Cycle Where is Real Time?
  • 9. 4/25/2017 9 Volume Variety Velocity ……….. Volume Volume is increasing at incredible rates. With more people using high speed internet connections than ever, plus the growth of IoT and always on devices these are causing this tremendous increase in Volume.
  • 10. 4/25/2017 10 Variety Next in breaking down Data into easily digestible bite-size chunks is the concept of Variety. Take your personal experience 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 Variety of information you personally create on a daily basis which is being collected and analyzed is simply overwhelming. Variety •FB generates 10TB daily •Twitter generates 7TB of data Daily •IBM claims 90% of today’s stored data was generated in just the last two years.
  • 11. 4/25/2017 11 Variety Big Data isn't just numbers, dates, and strings. Big Data is also geospatial data, 3D data, audio and video, and unstructured text, including log files and social media. Traditional database systems were designed to address smaller volumes of structured data, fewer updates or a predictable, consistent data structure. Streaming data and real-time analysis includes different types of data 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.
  • 12. 4/25/2017 12 Velocity • Clickstreams and ad impressions capture user behavior at millions of events per second • High-frequency stock trading algorithms reflect market changes within microseconds • Machine to machine processes exchange data between billions of devices • Infrastructure and sensors generate massive log data in real-time • On-line gaming systems support millions of concurrent users, each producing multiple inputs per second. But I Believe These are the Real Four
  • 13. 4/25/2017 13 The Structure of Data  Structured • Most traditional data sources  Semi-structured • Many sources of big data  Unstructured • Video data, audio data 25 Historical Development of Database Technology Early Database Applications: The Hierarchical and Network Models were introduced in mid 1960’s and dominated during the seventies. A bulk of the worldwide database processing still occurs using these models. Relational Model based Systems: The model that was originally introduced in 1970 was heavily researched and experimented with in IBM and the universities. Relational DBMS Products emerged in the 1980’s.
  • 14. 4/25/2017 14 Historical Development of Database Technology Object-oriented applications: OODBMSs were introduced in late 1980’s and early 1990’s to cater to the need of complex data processing in CAD and other applications. Data on the Web and E-commerce Applications: Web contains data in HTML (Hypertext markup language) with links among pages. This has given rise to a new set of applications and E-commerce is using new standards like XML (eXtended Markup Language). Extending Database Capabilities New functionality is being added to DBMSs in the following areas: – Scientific Applications – Image Storage and Management – Audio and Video data management – Data Mining – Spatial data management – Time Series and Historical Data Management – IoT – Streaming The above gives rise to new research and development in incorporating new data types, complex data structures, new operations and storage and indexing schemes in database systems.
  • 15. 4/25/2017 15 Top10 Time Series Databases • DalmatinerDB • InfluxDB • Prometheus • Riak TS • OpenTSDB • KairosDB • Elasticsearch • Druid • Blueflood • Graphite (Whisper)
  • 16. 4/25/2017 16 The Intelligence is in the Connections Connections between people ConnectionsbetweenInformation Email Social Networking Groupware Javascrip t Weblogs Databases File Systems HTTP Keyword Search USENET Wikis Websites Directory Portals 2010 - 2020 Web 1.0 2000 - 2010 1990 - 2000 PC Era 1980 - 1990 RSS Widgets PC’s 2020 - 2030 Office 2.0 XML RDF SPARQLAJAX FTP IRC SOA P Mashups File Servers Social Media Sharing Lightweight Collaboration ATOM Web 3.0 Web 4.0 Semantic Search Semantic Databases Distributed Search Intelligent personal agents Java SaaS Web 2.0Flash OWL HTML SGML SQL Gopher P2P The Web The PC Windows MacOS SWRL OpenID BBS MMO’s VR Semantic Web Intelligent Web The Internet Social Web Web OS Source: Gartner, Cisco, DSmith Big Challenge 24/7 Streaming Data It seems that everything in 2017 will have a sensor that sends information back to the mothership.
  • 17. 4/25/2017 17 The Ubiquity of Data Opportunities With vast amounts of data now available, companies in almost every industry are focused on exploiting data for competitive advantage. In the past, firms could employ teams of statisticians, modelers, and analysts to explore datasets manually, but the volume and variety of data have far outstripped the capacity of manual analysis. At the same time, computers have become far more powerful, networking has become ubiquitous, and algorithms have been developed that can connect datasets to enable broader and deeper analyses than previously possible. The convergence of these phenomena has given rise to the increasing widespread business application of data science principles and data mining techniques. 33 Data Science 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 34
  • 18. 4/25/2017 18 Data as a strategic asset “Groupon will not be the first or last organization to compete and win on the power of data. It’s happening everywhere.” Reid Hoffman and James Slavet Greylock Partners Data harnessing – data as renewable energy  Harnessing naturally occurring data streams  Like harnessing raw energy to be converted into usable energy  Conversion of raw data into usable data 35 Emergence of a Fourth Research Paradigm: Data Science Thousand years ago – – Experimental Science Description of natural phenomena Last few hundred years – – Theoretical Science Newton’s Laws, Maxwell’s Equations… Last few decades – – Computational Science Simulation of complex phenomena Today – – Data-Intensive Science Scientists overwhelmed with data!
  • 19. 4/25/2017 19 Key to Creating Artificial General Intelligence: Increasing Computational Power NNow = • Beating a mouse brain • About a thousandth of a human
  • 20. 4/25/2017 20 Information and Communication Trends • Seamless Interoperability Between Heterogeneous Networks • Mobility for All – Devices for All Things • User Centered Content-Based Information Access • Agents Take Over Routine Work • “E”- Processes for Business and Private Life • Human Computer Interaction is Turning Into Human Computer Cooperation • Human is not part of most computer and data interaction The “Fat Pipe”
  • 21. 4/25/2017 21 What is direction of DATA Walmart handles more than 1 million customer transactions every hour. • Facebook handles 40 billion photos from its user base. • Decoding the human genome originally took 10years to process; now it can be achieved in one week. “The market for enterprise AI systems will increase from $202.5 million in 2015 to $11.1 billion by 2024.” - Tractica
  • 22. 4/25/2017 22 Internet of Things: The Next Frontier Data available from “Internet of Things”
  • 23. 4/25/2017 23 IoT is generating massive volumes of structured and unstructured data, and an increasing share of this data is being deployed on cloud services. The data is often heterogeneous and lives across multiple relational and non-relational systems. When these smart devices are connected to intelligent applications such as Siri, Alexa ,Cortana or Google Home, the possibilities become endless. Conversational AI will enable high-level conversations with these intelligent applications These bots, per Microsoft CEO Satya Nadella, will be the next apps. 2017 will see the convergence of these intelligent applications with many IoT devices. As the world gets smarter, infrastructure demands will grow Smart traffic systems Smart water management Smart energy grids Smart healthcare Smart food systems Smart oil field technologies Smart regions Smart weather Smart countries Smart supply chains Smart cities Smart retail
  • 26. 4/25/2017 26 Will technological breakthroughs be developed in time to boost economic productivity and solve the problems caused by a growing world population, rapid urbanization, and climate change? Game Changer - Impact of New Technologies • The Internet of Things • Not just Big Data, but a zettaflood • Much D to D • Wisdom of the Data Science • The next 'Net • Move from physical to virtual • The world gets Bio • Regenerative Medicine Conclusion The Age of Data is here Data is the central business asset Data generation has changed forever • The World is moving to Real Time • Data Science is the Key Your legacy analytic software WILL fail in the Age of Data Crisis of software that scales to meet demand Streaming data changes the concept of data Think about where the data comes from Attempt to capture and analyze any data that might be relevant, regardless of where it resides Data Science is changing how data is: – Collected, discovered, analyzed, used, acted upon …
  • 27. 4/25/2017 27 In Parting: Be Paranoid “Sooner or later, something fundamental in your business world will change.”  Andrew S. Grove, Founder, Intel “Only the Paranoid Survive” Thank You David Smith dsmith@socialcare.com