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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?
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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!
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:
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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.