IS1825 Multimedia Development for Internet Applications Lecture 06: Big data and the Internet of...
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Transcript of IS1825 Multimedia Development for Internet Applications Lecture 06: Big data and the Internet of...
IS1825 Multimedia Development for Internet ApplicationsLecture 06: Big data and the Internet of ThingsRob Gleasure
[email protected]://corvus2.ucc.ie/phd/rgleasure/index.html
IS1825
Today’s session Introduction to big data The 3 V’s of big data The Internet of Things
Big data
The idea is that the vast amounts of interaction data allow for systems that are nuanced and responsive in ways that were previously not possible
Also a realisation that, if it can be analysed, this data is a huge commodity, meaning new business models are possible
So when is data ‘big data’
3 Vs of Big data
Volume Facebook generates 10TB of new data daily, Twitter 7TB A Boeing 737 generates 240 terabytes of flight data during a
flight from one side of the US to the other
We can use all of this data to tell us something, if we know the right questions to ask
3 Vs of Big data
From http://www.slideshare.net/ibmcanada/big-dataturning-data-into-insights?qid=0b4c69bc-3db2-4e12-ae47-a362a25752eb&v=qf1&b=&from_search=3
Traditional Approach Big Data Approach
Analyze small subsets of data
Analyze all data
Analyzedinformation
All available information
All available informationanalyzed
3 Vs of Big data
Velocity Clickstreams and asynchronous data transfer can capture what
millions of users are doing right now
Think back to AirBnB – make a change, then watch the response.
No guesswork required up front as to what to gather, we can induce the interesting stuff as we see it
3 Vs of Big data
From http://www.slideshare.net/ibmcanada/big-dataturning-data-into-insights?qid=0b4c69bc-3db2-4e12-ae47-a362a25752eb&v=qf1&b=&from_search=3
Start with hypothesis and test against selected data
Explore all data andidentify correlations
Hypothesis Question
DataAnswer
Exploration
CorrelationInsight
Traditional Approach Big Data Approach
Data
3 Vs of Big data
Variety Move from structured data to unstructured data, including image
recognition, text mining, etc. Gathered from users, applications, systems, sensors
Increasingly comprehensive data view of our ecosystem The Internet of Things
The Internet of Things
From http://www.pcworld.com/article/2039413/new-intel-ceo-creates-mysterious-new-devices-division.html
The Internet of Things
RFID sensors, bluetooth, microprocessors, wifi all becoming easier to embed in ‘dumb’ devices
Move to mobile also means more data streaming from us at all times, e.g. location, call activity, net use
The Internet of Things
Smart homes/smart cities Temperature, lighting, food stocks, energy, security
Smart cars Diagnostics, traffic suggestions, sensors, self-driving
Smart healthcare Worn and intravenous computing detects issues early and
monitors care outcomes remotely
Smart factories, farms Machines coordinated efficiently, linked dynamically to
consumption models
Big data
Success stories Books
Barnes and Noble: Discovered that readers often quit nonfiction books less than halfway through. Introduced highly successful new series of short books on topical themes
Amazon: originally used a panel of expert reviewers for books. Data surplus allowed them to create increasingly predictive recommendations. Panel has since been disbanded and 1/3 of sales are now driven by the recommender system
Big data and the Internet of Things Success stories (continued)
Transport Flyontime.us: used historical weather and flight delay
information to predict likelihood of flights get delayed Farecast: looked at ticket prices for specific flights based on
historical data, then advised users to buy or wait according to predicted fare costing trajectory
UPS: Uses a range of traffic data to calculate most efficient time/fuel efficient routes according to complex algorithm
Big data and the Internet of Things Famous success stories (continued)
Healthcare Modernizing Medicine EMA dermatology system
https://www.youtube.com/watch?v=jMGaGtK9nzU
Big data and the Internet of Things Famous success stories (continued)
Social media Google (data for information relevance) Twitter (c.f. #RescuePH) Facebook (social data)
Issues with big data
Google Flu Trends Life imitating data, imitating life?
No one is really average height
Your Xbox knows you like that Katy Perry song
Also, Target called to say your teenage daughter is pregnant.
Icecream sales and shark attacks…
From http://xkcd.com/552/
Icecream sales and shark attacks continued (correlation, not causation)
Target’s family monitoring continued
Readings
Mayer-Schönberger, V. and Cukier, K. (2014). Big Data: A Revolution That Will Transform How We Live, Work, and Think, John Murray Publishers, UK.
http://nextcity.org/daily/entry/rescuers-use-social-media-twitter-to-find-disaster-victims