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Copyright 2014 by Saurage Research, Inc. All rights reserved. No part of this document may be reproduced by any means whatsoever without permission in writing from Saurage Research, Inc.
Susan Saurage-Altenloh
October 2014
Bamboozled or Just Buried
by Big Data?
2
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• Definition
• History
• How big is it?
• The promise of big data
• The limits of big data
• Primary players
• What we are learning
• Uses and applications
Our Path Today
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• Big data are extremely large data sets that may be
analyzed computationally to reveal patterns, trends, and
associations, especially relating to human behavior and
interactions.
• Big data is an all-encompassing term for any collection
of data sets so large and complex that it becomes
difficult to process using traditional data processing
applications.
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Confusion
"...nobody seems quite sure exactly what the
phrase means, beyond a general impression of
the storage and analysis of unfathomable
amounts of information, but we are assured,
over and over, that it’s going to be big.“
--The New Yorker
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Just sayin’….
Big data is a vague term for a massive
phenomenon that has rapidly become an
obsession with entrepreneurs, scientists,
governments and the media.
-- Financial Times Magazine
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Growth, however, is not vague.
http://www.eweek.com/imagesvr_ce/eweek/images/stories/slideshows/036912_bigdata/02.jpg
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Historically Speaking
• Term “big data” gained
currency in 2008
• 2012 was crossover year to
use of big data
• Data expansion issues
began early 20th century
http://www.forbes.com/sites/gilpress/2013/05/09/a-very-short-history-of-big-data/
Images and timeline data points in this presentation extracted from http://www.winshuttle.com/big-data-timeline/
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The 1880 U.S. Census
took eight years to
tabulate!
First Big(ger) Data
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1989 – Business Intelligence
In 1989, Howard Dresner
defined BI as "concepts and
methods to improve business
decision making by using
fact-based support systems".
Not long after, companies
such as Business Objects,
Actuate, Crystal Reports, and
MicroStrategy began to
emerge, offering to report
and analyze company data.
Source: A Brief History of Decision Support
Systems by D.J. Power.
http://www.winshuttle.com/big-data-timeline
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1997: The term "big data" was used for the first time in an article by NASA
researchers Michael Cox and David Ellsworth. The pair claimed that the
rise of data was becoming an issue for current computer systems. This was
also known as the "problem of big data".
Source: Application-Controlled Demand Paging for Out-of-Core Visualization.
http://www.winshuttle.com/big-data-timeline
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2001 – The 3 V’s
Gartner Analyst Doug Laney published a research
paper titled 3D Data Management: Controlling Data
Volume, Velocity, and Variety. Even today, the “3Vs” are
the generally-accepted dimensions of big data.
http://www.winshuttle.com/big-data-timeline
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How big is it?
The reason scarcely anybody used to talk
about Big Data is that, until very recently, it
didn’t exist—most data had been, by current
standards, small potatoes. Now, Big Data is
mainly measured in terabytes (trillions) and
petabytes (quadrillions); within a decade,
even those numbers may seem quaint.
-- The New Yorker
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2007 – Zettabyte Defined
From Wikipedia, the free encyclopedia
The zettabyte is a multiple of the unit byte for digital information. The prefix
zetta indicates multiplication by the seventh power of 1000 or 1021 in the
International System of Units (SI). Therefore one zettabyte is one sextillion
(one long scale trilliard) bytes. The unit symbol is ZB.
1 ZB = 10007bytes = 1021bytes = 1000000000000000000000bytes = 1000exabytes = 1billionterabytes
A petabyte is the equivalent of 1,000 terabytes, or a quadrillion bytes. One
terabyte is a thousand gigabytes. One gigabyte is made up of a thousand
megabytes. There are a thousand thousand—i.e., a million—petabytes in a
zettabyte. Ouch.
http://www.winshuttle.com/big-data-timeline
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Seminal Article in Wired Magazine
http://www.winshuttle.com/big-data-timeline
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Google Flu Trends
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2009 – Business Intelligence Becomes a Priority
Source: Gartner.com
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2010 – ERP Arrives in the Cloud
http://www.winshuttle.com/big-data-timeline
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2011 – Growth of Data Storage at Enterprise Level
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Big Data Players
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2012 – Information Society Expands
http://www.winshuttle.com/big-data-timeline
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Growth Drivers
http://cdn.news-sap.com/wp-content/blogs.dir/1/files/SAP_Big_Data_E4.jpg
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2013 – Cloud ERP is Adopted Broadly
http://www.winshuttle.com/big-data-timeline
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Big Data Growth is Accelerating
http://www.tech-dynamics.com/solution-overview/big-data/
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Where do we go from here?
http://esj.com/articles/2014/07/10/big-data-analytics-moving-to-cloud.aspx
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2014 – The Future of Big Data
http://www.winshuttle.com/big-data-timeline
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The Promise of Big Data
Four claims:
• Data analysis produces uncannily
accurate results
• Every single data point can be captured,
making old statistical sampling techniques
obsolete
• It is passé to fret about what causes what,
because statistical correlation tells us
what we need to know
• Scientific or statistical models aren’t
needed because, “with enough data, the
numbers speak for themselves”
https://www.ft.com
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Dark Data
Information assets that organizations collect, process and store in the course
of their regular business activity, but generally fail to use for other purposes
Definition by Gartner
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The Limits of Big Data
• Statistics don’t lie
• Errors do exist
• Manual computations
required
• Complexity degrades
models
• Correlations differ from
causality
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Barriers to Capitalizing on Big Data
A big thanks to
Tata Consulting Services
http://sites.tcs.com/big-data-study
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Big Data Applications
http://i2mag.com/big-data-infographic/
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Branding, ROI and Big Data
Big data
builds
community
Big data
fosters culture
(customer and
employee
retention)
Big data
drives
revenue
Better
Decisions
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Returns on Big Data (emerging)
A big thanks to
Tata Consulting Services
http://sites.tcs.com/big-data-study
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Social Data Insights from Big Data
Real-time Market Mood
Relevant Issues and Content
User Interests
Internal Operational Metrics
Competitive Research
https://www.marketingtechblog.com
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BI and Online Marketing Integration
Incremental
Sales
Visitor to
Buyer Ratio
Tracking
Keywords
Social Media
Cost per
Lead
ROI
Sales of
Lead Source
Conversions
by
Campaign
The Basics
http://www.huffingtonpost.com/jayson-demers
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Big Data for Marketers in 2014
• 360 degree view of the customer
• The Internet of Things
• Data warehouse optimization
• Big data service refinery
• Information security
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It’s all about the insights and data!
ssaurage@SaurageResearch.com
http://pinterest.com/saurageresearch/
http://twitter.com/RealitySpikes
http://www.linkedin.com/company/saurage-research-inc.
https://www.facebook.com/SaurageMarketingResearch
http://www.saurageresearch.com/category/blog/
Explore the research possibilities:
37
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37
About the Presenter
Susan Saurage-Altenloh specializes in designing
research strategies and producing results that meet
clients' information needs – completely and exactly.
Susan has gathered actionable data for a client list that
includes nationally known medical facilities, large
manufacturers and refineries, prominent financial
institutions, municipal and national governmental
agencies, and advertising/ marketing firms.
The most notable ones – Tenet, Conoco, Cameron, the
EPA, HP/Compaq, Chicago Board of Trade, BP, Exxon,
Dow, Siemens Transmission Products and McDonald’s –
include several Fortune 500 companies.
Susan has authored several articles appearing in national
and regional business publications and regularly appears
on television as an expert in market information and
research trends. She is a graduate of the MBA program at
University of Texas at Austin and graduated Magna Cum
Laude from Houston Baptist University.

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Big Data - What the Heck?

  • 1. Copyright 2014 by Saurage Research, Inc. All rights reserved. No part of this document may be reproduced by any means whatsoever without permission in writing from Saurage Research, Inc. Susan Saurage-Altenloh October 2014 Bamboozled or Just Buried by Big Data?
  • 2. 2 IABC Southern Region Conference | 16 October 2014 2 • Definition • History • How big is it? • The promise of big data • The limits of big data • Primary players • What we are learning • Uses and applications Our Path Today
  • 3. 3 IABC Southern Region Conference | 16 October 2014 3 • Big data are extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions. • Big data is an all-encompassing term for any collection of data sets so large and complex that it becomes difficult to process using traditional data processing applications.
  • 4. 4 IABC Southern Region Conference | 16 October 2014 4 Confusion "...nobody seems quite sure exactly what the phrase means, beyond a general impression of the storage and analysis of unfathomable amounts of information, but we are assured, over and over, that it’s going to be big.“ --The New Yorker
  • 5. 5 IABC Southern Region Conference | 16 October 2014 5 Just sayin’…. Big data is a vague term for a massive phenomenon that has rapidly become an obsession with entrepreneurs, scientists, governments and the media. -- Financial Times Magazine
  • 6. 6 IABC Southern Region Conference | 16 October 2014 6 Growth, however, is not vague. http://www.eweek.com/imagesvr_ce/eweek/images/stories/slideshows/036912_bigdata/02.jpg
  • 7. 7 IABC Southern Region Conference | 16 October 2014 7 Historically Speaking • Term “big data” gained currency in 2008 • 2012 was crossover year to use of big data • Data expansion issues began early 20th century http://www.forbes.com/sites/gilpress/2013/05/09/a-very-short-history-of-big-data/ Images and timeline data points in this presentation extracted from http://www.winshuttle.com/big-data-timeline/
  • 8. 8 IABC Southern Region Conference | 16 October 2014 8 The 1880 U.S. Census took eight years to tabulate! First Big(ger) Data
  • 9. 9 IABC Southern Region Conference | 16 October 2014 9 1989 – Business Intelligence In 1989, Howard Dresner defined BI as "concepts and methods to improve business decision making by using fact-based support systems". Not long after, companies such as Business Objects, Actuate, Crystal Reports, and MicroStrategy began to emerge, offering to report and analyze company data. Source: A Brief History of Decision Support Systems by D.J. Power. http://www.winshuttle.com/big-data-timeline
  • 10. 10 IABC Southern Region Conference | 16 October 2014 10 1997: The term "big data" was used for the first time in an article by NASA researchers Michael Cox and David Ellsworth. The pair claimed that the rise of data was becoming an issue for current computer systems. This was also known as the "problem of big data". Source: Application-Controlled Demand Paging for Out-of-Core Visualization. http://www.winshuttle.com/big-data-timeline
  • 11. 11 IABC Southern Region Conference | 16 October 2014 11 2001 – The 3 V’s Gartner Analyst Doug Laney published a research paper titled 3D Data Management: Controlling Data Volume, Velocity, and Variety. Even today, the “3Vs” are the generally-accepted dimensions of big data. http://www.winshuttle.com/big-data-timeline
  • 12. 12 IABC Southern Region Conference | 16 October 2014 12 How big is it? The reason scarcely anybody used to talk about Big Data is that, until very recently, it didn’t exist—most data had been, by current standards, small potatoes. Now, Big Data is mainly measured in terabytes (trillions) and petabytes (quadrillions); within a decade, even those numbers may seem quaint. -- The New Yorker
  • 13. 13 IABC Southern Region Conference | 16 October 2014 13 2007 – Zettabyte Defined From Wikipedia, the free encyclopedia The zettabyte is a multiple of the unit byte for digital information. The prefix zetta indicates multiplication by the seventh power of 1000 or 1021 in the International System of Units (SI). Therefore one zettabyte is one sextillion (one long scale trilliard) bytes. The unit symbol is ZB. 1 ZB = 10007bytes = 1021bytes = 1000000000000000000000bytes = 1000exabytes = 1billionterabytes A petabyte is the equivalent of 1,000 terabytes, or a quadrillion bytes. One terabyte is a thousand gigabytes. One gigabyte is made up of a thousand megabytes. There are a thousand thousand—i.e., a million—petabytes in a zettabyte. Ouch. http://www.winshuttle.com/big-data-timeline
  • 14. 14 IABC Southern Region Conference | 16 October 2014 14 Seminal Article in Wired Magazine http://www.winshuttle.com/big-data-timeline
  • 15. 15 IABC Southern Region Conference | 16 October 2014 15 Google Flu Trends
  • 16. 16 IABC Southern Region Conference | 16 October 2014 16 2009 – Business Intelligence Becomes a Priority Source: Gartner.com
  • 17. 17 IABC Southern Region Conference | 16 October 2014 17 2010 – ERP Arrives in the Cloud http://www.winshuttle.com/big-data-timeline
  • 18. 18 IABC Southern Region Conference | 16 October 2014 18 2011 – Growth of Data Storage at Enterprise Level
  • 19. 19 IABC Southern Region Conference | 16 October 2014 19 Big Data Players
  • 20. 20 IABC Southern Region Conference | 16 October 2014 20 2012 – Information Society Expands http://www.winshuttle.com/big-data-timeline
  • 21. 21 IABC Southern Region Conference | 16 October 2014 21 Growth Drivers http://cdn.news-sap.com/wp-content/blogs.dir/1/files/SAP_Big_Data_E4.jpg
  • 22. 22 IABC Southern Region Conference | 16 October 2014 22 2013 – Cloud ERP is Adopted Broadly http://www.winshuttle.com/big-data-timeline
  • 23. 23 IABC Southern Region Conference | 16 October 2014 23 Big Data Growth is Accelerating http://www.tech-dynamics.com/solution-overview/big-data/
  • 24. 24 IABC Southern Region Conference | 16 October 2014 24 Where do we go from here? http://esj.com/articles/2014/07/10/big-data-analytics-moving-to-cloud.aspx
  • 25. 25 IABC Southern Region Conference | 16 October 2014 25 2014 – The Future of Big Data http://www.winshuttle.com/big-data-timeline
  • 26. 26 IABC Southern Region Conference | 16 October 2014 26 The Promise of Big Data Four claims: • Data analysis produces uncannily accurate results • Every single data point can be captured, making old statistical sampling techniques obsolete • It is passé to fret about what causes what, because statistical correlation tells us what we need to know • Scientific or statistical models aren’t needed because, “with enough data, the numbers speak for themselves” https://www.ft.com
  • 27. 27 IABC Southern Region Conference | 16 October 2014 27 Dark Data Information assets that organizations collect, process and store in the course of their regular business activity, but generally fail to use for other purposes Definition by Gartner
  • 28. 28 IABC Southern Region Conference | 16 October 2014 28 The Limits of Big Data • Statistics don’t lie • Errors do exist • Manual computations required • Complexity degrades models • Correlations differ from causality
  • 29. 29 IABC Southern Region Conference | 16 October 2014 29 Barriers to Capitalizing on Big Data A big thanks to Tata Consulting Services http://sites.tcs.com/big-data-study
  • 30. 30 IABC Southern Region Conference | 16 October 2014 30 Big Data Applications http://i2mag.com/big-data-infographic/
  • 31. 31 IABC Southern Region Conference | 16 October 2014 31 Branding, ROI and Big Data Big data builds community Big data fosters culture (customer and employee retention) Big data drives revenue Better Decisions
  • 32. 32 IABC Southern Region Conference | 16 October 2014 32 Returns on Big Data (emerging) A big thanks to Tata Consulting Services http://sites.tcs.com/big-data-study
  • 33. 33 IABC Southern Region Conference | 16 October 2014 33 Social Data Insights from Big Data Real-time Market Mood Relevant Issues and Content User Interests Internal Operational Metrics Competitive Research https://www.marketingtechblog.com
  • 34. 34 IABC Southern Region Conference | 16 October 2014 34 BI and Online Marketing Integration Incremental Sales Visitor to Buyer Ratio Tracking Keywords Social Media Cost per Lead ROI Sales of Lead Source Conversions by Campaign The Basics http://www.huffingtonpost.com/jayson-demers
  • 35. 35 IABC Southern Region Conference | 16 October 2014 35 Big Data for Marketers in 2014 • 360 degree view of the customer • The Internet of Things • Data warehouse optimization • Big data service refinery • Information security
  • 36. 36 IABC Southern Region Conference | 16 October 2014 36 It’s all about the insights and data! ssaurage@SaurageResearch.com http://pinterest.com/saurageresearch/ http://twitter.com/RealitySpikes http://www.linkedin.com/company/saurage-research-inc. https://www.facebook.com/SaurageMarketingResearch http://www.saurageresearch.com/category/blog/ Explore the research possibilities:
  • 37. 37 IABC Southern Region Conference | 16 October 2014 37 About the Presenter Susan Saurage-Altenloh specializes in designing research strategies and producing results that meet clients' information needs – completely and exactly. Susan has gathered actionable data for a client list that includes nationally known medical facilities, large manufacturers and refineries, prominent financial institutions, municipal and national governmental agencies, and advertising/ marketing firms. The most notable ones – Tenet, Conoco, Cameron, the EPA, HP/Compaq, Chicago Board of Trade, BP, Exxon, Dow, Siemens Transmission Products and McDonald’s – include several Fortune 500 companies. Susan has authored several articles appearing in national and regional business publications and regularly appears on television as an expert in market information and research trends. She is a graduate of the MBA program at University of Texas at Austin and graduated Magna Cum Laude from Houston Baptist University.