Data and Analytics

1. INLS 151
mon nov 2
today’s line-up
Pecha Kucha
presentation format for
data-to-story project
20 slides, 20 seconds each (auto advance)
look at presentation dates
example
tips
online privacy
brief intro to “big data”
Right to be forgotten video
discussion questions (from you)
ethics cases – small group discussion

2. Team Members Topic
Presentation
Date
Josh, Michelle & Samantha Voting behavior + demographics
Katie, Lucas, Jenny & Duncan
Voting behavior + source of news information
+ demographics
Michaela Environmental concerns + age
Mel’leeah, Aaron, Winta &
Micheline
Age at parenthood and general happiness
Kaitlin Attitude toward right to die and gender
Chris, Ben & Ryan Family income and general happiness
Rashaad, Chase, Alexis &
Abigail
Attitude toward legalization of marijuana and
age
Travis, Thomas & Michael
Belief in an afterlife + gender + general
happiness
Maudrie, Kate, Yunhan &
Wanyi
Attitude toward capital punishment, gender
+ political party affiliation
Presentation options: Wed, Nov 18; Mon Nov 23; Mon Nov 30

3. Pecha kucha presentation
https://www.youtube.com/watch?v=wGaCLWaZLI4
20 slides, 20 seconds each = about 7 minutes

4. Short presentation format tips
• Bait audience, catchy hook, why should we care?
• Tell us what you are going to tell us…
• Relevant images (graphs, charts, photos, clip art)
• Main point in a short phrase
• Script + practice, practice, practice
• Cite your sources (corresponding slide or at end)
• Energy, enthusiasm, & eye contact
• Do enough prep that you are comfortable
• Anticipate & prepare for questions

5. What do we mean by privacy?
• Louis Brandeis (1890)
– “right to be left alone”
– protection from institutional threat:
government, press
– Supreme Court justice
• Alan Westin (1967)
– legal scholar, modern right to privacy
– “right to control, edit, manage, and delete
information about themselves and decide
when, how, and to what extent
information is communicated to others”
Privacy and Freedom, 1967

6. Privacy vs. security
• Security helps enforce privacy policies
• Can be at odds with each other
– e.g., invasive screening to make us
more “secure” against terrorism
Privacy: what information goes where?
Security: protection against
unauthorized access

7. DEFINITION: “Big Data”
Big Data is used in the singular and refers to a collection of data sets so
large and complex, it’s impossible to process them with the usual
databases and tools. Because of its size and associated numbers, Big
Data is hard to capture, store, search, share, analyze and visualize.
The phenomenon came about in recent years due to the sheer amount
of machine data being generated today – thanks to mobile devices,
tracking systems, RFID, sensor networks, social networks, Internet
searches, automated record keeping, video archives, e-commerce, etc.
– coupled with the additional information derived by analyzing all this
information, which on its own creates another enormous data set.
Companies pursue Big Data because it can be revelatory in spotting
business trends, improving research quality, and gaining insights in a
variety of fields, from IT to medicine to law enforcement and
everything in between and beyond.

8. Massive Messy Data
• Big Data analysis requires collecting
– massive amounts of
– messy data
• Messy data: The data is not in a uniform format as one
would see in traditional database, it is not annotated
(semantically tagged)
– technological breakthroughs allow us to find ways to
manipulate and analyze such data.
• Massive amounts: think of every tweet ever tweeted.
They are all in the Library of Congress (a project that may
be failing, imagine 400 million tweets a day in 2013.

9. Patterns We Would Not Notice
• Big Data analytics can reveal important patterns that would
otherwise go unnoticed.
• Taking the antidepressant Paxil together with the anti-
cholesterol drug Pravachol could result in diabetic blood sugar
levels. Discovered by
– (1) using a symptomatic footprint characteristic of very high blood
sugar levels obtained by analyzing thirty years of reports in an FDA
database, and
– (2) then finding that footprint in the Bing searches using an algorithm
that detected statistically significant correlations. People taking both
drugs also tended to enter search terms (“fatigue” and “headache,”
for example) that constitute the symptomatic footprint.

10. DEFINITION: “Cookie”
A cookie is a small amount of data generated by a website and saved by your
browser. Its purpose is to remember information about you, similar to a
preference file created by a software application. Cookies are also used to store
user preferences for a specific site. For example, search engines like Google or
Bing store your searches. Financial websites sometimes use cookies to store
recently viewed stock quotes. If a website needs to store a lot of personal
information, it may use a cookie to remember who you are, but will load the
information from its server.
Browser cookies come in two different flavors: "session" and "persistent." Session
cookies are temporary and are deleted when the browser is closed. These types of
cookies are often used by e-commerce sites to store items placed in your
‘shopping cart,’ and can serve many other purposes as well. Persistent cookies
are designed to store data for an extended period of time. Each persistent cookie
is created with an expiration date, which may be anywhere from a few days to
several years in the future. Once the expiration date is reached, the cookie is
automatically deleted.

11. DEFINITION: “RFID”
RFID stands for Radio Frequency IDentification, a technology that uses tiny
computer chips smaller than a grain of sand to track items at a distance. RFID
chips have been hidden in the packaging of Gillette razor products and in other
products you might buy at a local Wal-Mart, Target, or Costco - and they are
already being used to “spy” on people. Each tiny chip is hooked up to an antenna
that picks up electromagnetic energy beamed at it from a reader device. When it
picks up the energy, the chip sends back its unique identification number to the
reader device, allowing the item to be remotely identified. These chips can beam
back information anywhere from a couple of inches to up to 20 or 30 feet away.
Shown at left is a magnified image of actual RFID tag found
in Gillette Mach3 razor blades. The chip appears as the tiny
black square. The coil of wires surrounding the chip is the
antenna, which transmits your information to a reader
device, which can be located anywhere!

12. DEFINITION: “RFID” (continued)
This technology is rapidly evolving and becoming more sophisticated. Now
RFID chips can even be printed, meaning the dot on a printed letter "i" could
be used to track you.
Companies are even experimenting with making the product packages
themselves serve as antennas. RFID chips can be well hidden. For example
they can be sewn into the seams of clothes, sandwiched between layers of
cardboard, and molded into plastic or rubber. Unlike a bar code, these
chips can be read from a distance, right through your clothes, wallet,
backpack or purse -- without your knowledge or consent -- by anybody with
the right reader device.
Many large corporations, including Philip Morris, Procter and Gamble, and
Wal-Mart, have begun experimenting with RFID chip technology and have
recently placed an order for up to 500 million RFID tags from a company
called Alien Technology.

13. Speaking of miniaturization…..
(a slight digression)
• Smartphones and tablets outsold desktop and laptop
computers in 2014; 170 million smartphones in U.S. 2014*
• The phone in your pocket has more programmable memory,
more storage and more capability than several large IBM
computers.
• It takes dozens of microprocessors running 100 million lines of
code to get a premium car out of the driveway, and this
software is only going to get more complex. In fact, the cost
of software and electronics accounts for 30-40% of the price.
*Statistia

14. What is collecting all this data?
Web Browsers Search Engines
Microsoft’s
Internet Explorer
Mozilla’s FireFox
Google’s Chrome
Apple’s Safari
Google’s
Microsoft
Yahoo’s
IAC Search’s
Time-Warner’s AOL
Explorer
(Non-profit foundation,
used to be Netscape)

15. What is collecting all this data?
Smartphones & Apps
Apple’s iPhone
(Apple O/S)
Samsung, HTC.
Nokia, Motorola
(Android O/S)
RIM Corp’s Blackberry
(BlackBerry O/S)
Tablet Computers & Apps
Apple’s iPad
Samsung’s
Galaxy
Amazon’s Kindle Fire

16. What is collecting all this data?
Games Boxes and GPS Systems Internet Service Providers

17. What is collecting all this data?
Smart TVs and Blu-Ray Players with
built-in Internet connectivity
Movie Rental Sites

18. What is collecting all this data?
Hospitals & Other Medical Systems Banking & Phone Systems
Can you hear me now?
(Heh heh heh!)
Pharmacies
Laboratories
Imaging Centers
Emergency Medical Services (EMS)
Hospital Information Systems
Doc-in-a-Box
Electronic Medical Records
Blood Banks
Birth & Death Records

19. What is collecting all this data?
A real pain in the apps! What are they collecting?
• Restaurant reservations
(Open Table)
• Weather in L.A. in 3 days
(Weather+)
• Side effects of medications
(MedWatcher)
• 3-star hotels in New Orleans
(Priceline)
• Which PC should I buy and where
(PriceCheck)

20. Who is collecting all of this data?
Government Agencies Big Pharmaceutical Companies

21. Who is collecting all this data?
Consumer Products Companies Big Box Stores

22. Who is collecting what?
Credit Card Companies What data are they getting?
Restaurant check
Grocery Bill
Airline ticket
Hotel Bill

23. Why are they collecting all this data?
Target Marketing
• To send you catalogs for
exactly the merchandise
you typically purchase.
• To suggest medications that
precisely match your
medical history.
• To “push” television
channels to your set instead
of your “pulling” them in.
• To send advertisements on
those channels just for you!
Targeted Information
• To know what you need
before you even know you
need it based on past
purchasing habits!
• To notify you of your
expiring driver’s license or
credit cards or last refill on a
Rx, etc.
• To give you turn-by-turn
directions to a shelter in
case of emergency.

24. Examples of big data…..
Walmart handles more than 1 million customer transactions
every hour, which is imported into databases estimated to
contain more than 2.5 petabytes of data — the equivalent
of 167 times the information contained in all the books in
the US Library of Congress.
FICO Credit Card Fraud Detection System protects 2.1 billion
active accounts world-wide.
The volume of business data worldwide, across all
companies, doubles every 1.2 years, according to estimates

25. Examples of Big Data
With a smart meter, a utility company goes from collecting
one data point a month per customer (using a meter
reader in a truck or car) to receiving 3,000 data points for
each customer each month, while smart meters send
usage information up to four times an hour.
One small Midwestern utility is using smart meter data to
structure conservation programs that analyze existing
usage to forecast future use, price usage based on demand
and share that information with customers who might
decide to forestall doing that load of wash until they can
pay for it at the nonpeak price.

26. Examples of Big Data
Global position satellite technology now allows trucking
firms to track their trucks - and the merchandise inside
them. Practically anything you can attach an RFID tag to
can be tracked. How a company uses that information – to
re-route trucks to create efficient routes, alert customers
to deliveries, and forecast and price services – depends on
the ability to manage and analyze data effectively.

27. Big Brother Needs Big Data
In March 2012, the Obama Administration announced the
Big Data Research and Development Initiative, $200 million
in new R&D investments, which will explore how Big Data
could be used to address important problems facing the
government. The initiative was composed of 84 different Big
Data programs spread across six departments.
http://tinyurl.com/85oytkj

28. What are some impacts of Big Data?
• Decisions like your credit score and your
insurance rates may be based on the analysis
of big data, for good or bad.
• After Haiti’s 2010 earthquake, Columbia
University tracked the movements of 2 million
refugees by the SIM cards in their cell phones
and were able to determine where health
risks would likely develop.

29. Is Big Data good or bad for
consumers?
• How would you feel about paying more for the
same product than the person checking out in
front of you?
• The real challenge: are you willing to get
better value and more innovation for some
loss of privacy?
• Since there is no way to stop the accumulation
of Big Data, should its use be regulated by the
Federal government?

30. “Right to be forgotten”
Via European courts: residents can ask corporations
like Google to delete those unflattering posts,
photos and other online material from online search
results
Paul F. Nemitz is the director for
fundamental rights and union
citizenship of the European
Commission's Directorate General
for Justice and Consumers.
Eric Posner is the Kirkland and
Ellis Distinguished Service
Professor of Law at the University
of Chicago
YES, right to be forgotten
Andrew McLaughlin is CEO of Digg
and Instapaper and a partner at
Betaworks. From 2009-11, he was a
member of Obama's senior White
House staff. Former director of global
public policy at Google.
Jonathan Zittrain is the George
Bemis Professor of Law at Harvard
Law School and the Kennedy School
of Government
NO, right to be forgotten
Through 12:20

31. How Can You Avoid Big Data?
• Pay cash for everything!
• Never go online!
• Don’t use a telephone!
• Don’t use Kroger or Harris Teeter cards!
• Don’t fill any prescriptions!
• Never leave your house!