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Big Data
Yasin Zamani
Yasin.Zamani@gmail.com
PhD Candidate of Artificial Intelligence
Image Processing Lab (Prof. S.Kasaei)
Sharif University of Technology
What is Big Data?
2
3
1
"The number of transistors incorporated in a chip will
approximately double every 24 months.“
--Gordon Moore, Intel co-founder
4
Excel’s Limit
Feature Maximum limit
Open
workbooks
Limited by available
memory and system
resources
Worksheet size 65,536 rows by 256 columns
Column width 255 characters
Row height 409 points
Feature Maximum limit
Open
workbooks
Limited by available memory
and system resources
Worksheet size 1,048,576 rows by 16,384 columns
Column width 255 characters
Row height 409 points
Excel 2003
Excel 2007
5
6
Iris Data
Petal
Sepal
7
Iris Data
8
9
• 6,000 tweets per
second
• 500 million tweets per
day
• 200 billion tweets per
year
10
Structured Data
11
Unstructured Data
12
NoSQL : Not Only SQL Data
13
Does big data need all three?
14
How is Big Data Used?
15
16
Siri
17
Amazon
18
Netflix
19
IMDB
20
21
Advertisement
22
Predictive Marketing
Predicts major life events
Looks at consumer behavior
Uses demographic info
Can purchase more data
23
Predict Trends
24
Fraud Detection
Point of sale
Geolocation and IP address
Login time
Biometrics
25
26
27
Big Data and Data Science
28
The three facets of data science
29
30
31
32
33
34
35
Sources of Big Data
36
37
Intentional Data
Photos, videos, audio
Text on social network
Clicking “Like”
Web searches
38
Intentional Data
Webpages bookmarked
Emails and text messages
Cell phone calls
Online purchases
39
Metadata
Data about data
“Second order” data
Machine readable
40
Photograph Exif Metadata
41
Email Metadata
From, To, CC, and timestamp
42
Immersion
43
Sources
Cell phones connecting to towers
Satellite radio and GPS connecting
RFID readings
Readings from medical devices
44
The Internet of Things (IoT)
45
Storing Big Data
46
Local Storages
47
Cloud Storages
48
Cloud Computing
49
Preparing Data for Analysis
50
Challenges with Data Quality
51
Nearly 95% of spreadsheets
have errors.
Possible Errors
Incomplete or corrupted data
Duplicate records
Typographical errors
Data that is missing context
52
53
54
55
Big Data Analysis
56
Visualization
Humans as Visual Animals
Computers excel at predictive models.
Computers excel at data mining.
Humans perceive and interpret better.
Human vision still plays an important role.
57
What Humans Do Well
Identifying visual patterns
Identifying anomalies
Seeing patterns across groups
Interpreting content of images
58
Gestalt Patterns
59
60
61

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Big Data

Editor's Notes

  1. Dan Ariely (professor of behavioral economics at Duke University) …everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it...“ Doug Laney in 2001 three V's of volume, velocity, and variety.
  2. Obviously this is a relative definition.
  3. physical capacity and performance of computers double about every two years.
  4. over a million
  5. Iris data collected by Edgar Anderson analyzed by Ronald Fisher both of whom published their papers in 1936 This data set contains four measurements: The widths and lengths of the petals and sepals for three species of Iris. It's got about 150 cases
  6. hasn't changed in nearly 80 years
  7. fire hose
  8. One researcher has estimated that 80 percent of enterprise data may be unstructured
  9. semi – structured Xml – Extensible Markup Language Json - JavaScript Object Notation In fact, a recent study by Forester Research shows that variety is the biggest factor that's leading companies to big data solutions. In fact, variety was mentioned over four times as often as data volume.
  10. you can't use your standard approach
  11. advertising or marketing
  12. ad - informal an advertisement
  13. retailers lose about $3.5 billion dollars each year to online fraud insurance fraud, not counting health insurance, is estimated to be more than $40 billion dollars per year
  14. NIH - National Institutes of Health NASA - National Aeronautics and Space Administration
  15. scholarship and research
  16. Drew Conway in 2010
  17. Exif = Exchangeable image file format meta data that comes from a picture on an iPhone Time GPS altitude, latitude, longitude and position GPS image direction
  18. Immerse = to put someone or something deep into a liquid so that they are completely covered
  19. Radio-frequency identification (RFID)
  20. Now, it's estimated that by 2020, which is only a few years from now, as many as 30 billion uniquely identifiable devices may be connected to the internet.
  21. They're all in the same physical space There's usually only one copy it doesn't do anything about sharing
  22. Infrastructure as a service (IaaS) Platform as a service (PaaS) Software as a service (SaaS) Data as a service (DaaS)
  23. GIGO, for garbage in, garbage out
  24. You may recall the Mars climate orbiter that NASA launched back in 1998 at a cost of nearly $300 million and it crashed when it approached Mars a year later because some of the flight programming data had not been converted to metric units.
  25. Data starts and ends in Hadoop. Hadoop can handle different formats.
  26. German: Gestalt "shape, form" Reification
  27. National Science Foundation (NSF)