Big data burst upon the scene in the first decade of the 21st century, and the first organizations to embrace it were online and startup firms. Arguably, firms like Google, eBay, LinkedIn, and Facebook were built around big data from the beginning. Here is a brief introduction to what Big Data entails and how it could effect businesses today.
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
Introduction to Big Data
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2. Agenda
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What is Big Data
Example of Big Data
Drivers of Big Data: HIPO vs “Geeks”
Potential of Big Data
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eMOT | MG 8783: Cloud Computing
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3. What is Big Data?
• Three V’s of Big Data
– Volume
– Velocity
– Variety
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4. VOLUME: HOW MUCH DATA?
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6. Volume: How Much Data?
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KiloMegaTeraGigaPetaExaZettaYotta-
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: 10^3
: 10^6
: 10^9
: 10^12
: 10^15
: 10^18
: 10^21
: 10^24
bytes
bytes
bytes
bytes
bytes
bytes
bytes
bytes
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As of 2013
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7. Volume: How Much Data? (cont.)
HELLA(~ 10^27 byte)
aka
“HELLUVA-”
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8. Volume: How Much Data? (cont.)
If we were to take all that information and store
it in books, we could cover the entire area of the
US or China in 3 layers of books.
Martin Hilbert, Researcher, USC
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9. VELOCITY: IMMEDIATE & REACTIVE
(REAL-TIME DATA ANALYSIS)
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10. NYSE collects over 1 TB of trade info EACH session
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11. Modern cars have over HUNDRED sensors
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21. Variety: Data In What Form?
• Goal
– Identify patterns
– Gain insights
• Why?
– Combine big data with traditional data to better
understand pain points
– Mitigate/limit negative impact
– Increase/create revenue stream
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22. THREE V’S + 1 = VERACITY
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23. Role of Data Scientist
• Keep data organized - accurately
• Poor data management quality cost U.S.
economy roughly $3.1 trillion/year
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24. Role of Data Scientist (cont.)
• Data used correctly could spark limitless
potentials
– Prevent disease
– Combat crime
– Revolutionize global R&D
– Disrupt conventional business model
– Challenge HIPO’s guts
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25. Role of Data Scientist (cont.)
• Data used correctly could spark limitless
potentials
– Prevent disease
– Combat crime
– Revolutionize global R&D
– Disrupt conventional business model
–Challenge HIPO’s guts
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26. DRIVERS OF BIG DATA: HIPO VS
“GEEKS” (EXAMPLE)
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28. HIPO vs Geek
Michael Slaby, CTO, OFA 2008
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Harper Reed, CTO, OFA 2012
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29. Breakdown
• Innovative solution by leveraging big data
– Facebook information
• Personal interest: Preferences
• Location: Hyper-local, better content distribution
• Relevant: Contact efficiency
– Push innovation into sales by using data to have a
conversation
– Twitter
• DM via President and First Lady’s Twitter accounts
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32. Limitless
• Research by McKinsey in Jan 2013
– Companies using large-scale big data to shape
corporate strategy
• Example:
– IBM acquiring Kenexa Corp.
» Cloud (SAAS foundation) + big data (market insights)
» Remove “guess work” – replacing it with precision
• Hiring – Utilize behavioral traits
• Research by Harvard School of Public Health
– Big data could effectively prevent TB and
shrinkage of health care cost
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33. Harper’s Thought On Healthcare.gov
Source NYT.com
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