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Big Data: Data Analysis Boot CampIntroduction and Overview
Chuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhDChuck Cartledge, PhD
19 January 201819 January 201819 January 201819 January 201819 January 201819 January 201819 January 201819 January 201819 January 201819 January 201819 January 201819 January 201819 January 201819 January 201819 January 201819 January 201819 January 201819 January 201819 January 201819 January 201819 January 2018
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Table of contents (1 of 1)
1 IntroductionThe global view
2 OverviewThe world from 50,000feet.
3 AdministriviaMiscellaneous andnecessary things
4 Q & A
5 Conclusion
6 References
7 Vita
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The global view
Big Data: Data Analysis Boot Camp
We will cover aspects common toall Big Data investigations,including: defining Big Data,surveying tools and techniquesfor processing Big Data, andvisualizing selected aspects ofBig Data.The emphasis of the camp is tounderstand what is Big Datadata analysis beyond themarketing hype of the 3Vs ofvolume, variety, and velocity,
Image from [1].
More detailed information at:https://www.odu.edu/cepd/bootcamps/data-analysis
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The world from 50,000 feet.
Things we’ll be covering over the next three days:
Friday1 Administrivia2 What is BD?3 What is R?4 Looking at the built-in
iris and Titanic datasetsSaturday
1 Visualizing data withdifferent packages
2 Exploring cluster analysis(of different types)
3 Linear regression andsome variants
4 Classification techniques5 Text analysis6 Serial vs. parallel
processing
Sunday1 R limitations2 R and Hadoop3 R and SQL and No-SQL
DBMs4 Hands-on with real-world
crime data5 Wrap-up
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Miscellaneous and necessary things
All things related to paper work.
Parking – front and backwithout permitsBreaks – yes we’ll have them.Lunch – yes places near by:right a main light to “fast food”Text books – recommended butnot necessary, has good ideas,techniquesNon-credit optionCredit option – two additionalassignment
Hours – 9AM to 5PM withbreak for lunchSunday access – yes check inwith securitySoft copies – all presentations,and software are availableComputer logins and passwords– will be coordinatedBreak room – across hallBathrooms – around elevator
Other things as well.
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Miscellaneous and necessary things
Soft copies available from Internet
All information(presentations, scripts, anddata) is available on yourVM desktop (static)
All information is availablevia the I’net (dynamic)
Errata updated nightly
I’m not a web designer, nor do Iplay one on TV.
http://www.cs.odu.edu/
~ccartled/Teaching/
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Miscellaneous and necessary things
Same image.
http://www.cs.odu.edu/~ccartled/Teaching/
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Q & A time.
Q: What is the square root of4b2?A: To be or not to be.
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What have we covered?
Where we are.Where we’re going.How we’ll get there.
Now!! On to exploring the world of Big Data!
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References (1 of 1)
[1] Vangie Beal, Big Data,https://www.webopedia.com/TERM/B/big_data.html,2017.
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Who am I?
Father
Husband (only 41 years, but it seemslonger)
PhD, Computer Science, 2014
CAPT, USN retired 2004 (31+ years)
Professional software developer (38 years)
A perennial student
1st computer: 1970, donated ICBMguidance computer, machine code,paper/mylar tape, and drum memory
Interests: autonomic systems, real–time applications, distributed processing,long-term preservation of digital data, Big Data