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Big Data Visualization
Ugur Kadakal, PhD
Founder and CEO
Pagos, Inc.
What is Big Data?
“Big data is an all-encompassing term for any
collection of data sets so large and complex that
it becomes difficult to process using traditional
data processing applications.”
Wikipedia
http://en.wikipedia.org/wiki/Big_data
“Big data refers to datasets whose size is beyond
the ability of typical database software tools to
capture, store, manage, and analyze. This
definition is intentionally subjective and
incorporates a moving definition of how big a
dataset needs to be in order to be considered big
data—i.e., we don’t define big data in terms of
being larger than a certain number of terabytes
(thousands of gigabytes).”
McKinsey
http://www.mckinsey.com/insights/business_technology/big_data_
the_next_frontier_for_innovation
“While the use of the term is quite nebulous and
is often co-opted for other purposes, I’ve
understood “big data” to be about analysis for
data that’s really messy or where you don’t know
the right questions or queries to make — analysis
that can help you find patterns, anomalies, or
new structures amidst otherwise chaotic or
complex data points.”
Philip Ashlock
Chief Architect
Data.gov
http://datascience.berkeley.edu/what-is-big-data/
“Historically, most decisions — political,
military, business, and personal — have been made
by brains [that] have unpredictable logic and
operate on subjective experiential evidence. “Big
data” represents a cultural shift in which more
and more decisions are made by algorithms with
transparent logic, operating on documented
immutable evidence. I think “big” refers more to
the pervasive nature of this change than to any
particular amount of data.”
Daniel Gillick
Senior Research Scientist
Google
http://datascience.berkeley.edu/what-is-big-data/
“What’s “big” in big data isn’t necessarily the
size of the databases, it’s the big number of
data sources we have, as digital sensors and
behavior trackers migrate across the world. As we
triangulate information in more ways, we will
discover hitherto unknown patterns in nature and
society — and pattern-making is the wellspring of
new art, science, and commerce.”
Quentin Hardy
Deputy Tech Editor
The New York Times
http://datascience.berkeley.edu/what-is-big-data/
“To me, “big data” is the situation where an
organization can (arguably) say that they have
access to what they need to reconstruct,
understand, and model the part of the world that
they care about. Using their big data, then, they
can (try to) predict future states of the world,
optimize their processes, and otherwise be more
effective and rational in their activities”
Harlan Harris
Director
Data Science at Education Advisory Board
http://datascience.berkeley.edu/what-is-big-data/
“The joke is that big data is data that breaks
Excel, but we try not to be snooty about whether
you measure your data in MBs or PBs. Data is more
about your team and the results they can get.”
Brian Wilt
Senior Data Scientist
Jawbone
http://datascience.berkeley.edu/what-is-big-data/
“You cannot give me too much data. I see big data
as storytelling — whether it is through
information graphics or other visual aids that
explain it in a way that allows others to
understand across sectors. I always push for the
full scope of the data over averages and
aggregations — and I like to go to the raw data
because of the possibilities of things you can do
with it.”
Mike Cavaretta
Data Scientist and Manager
Ford Motor COmpany
http://datascience.berkeley.edu/what-is-big-data/
“Big data, which started as a technological
innovation in distributed computing, is now a
cultural movement by which we continue to
discover how humanity interacts with the world —
and each other — at large-scale.”
Drew Conway
Head of Data
Project Florida
http://datascience.berkeley.edu/what-is-big-data/
“Big Data is nothing more than a tool for
capturing reality — just as newspaper reporting,
photography and long-form journalism are. But
it’s an exciting tool, because it holds the
potential of capturing reality in some clearer
and more accurate ways than we have been able to
do in the past”
David Leonhardt
Editor
The Upshot, The New York Times
http://datascience.berkeley.edu/what-is-big-data/
BIG DATA vs SMALL DATA
DATA SOURCES
Small Data
• CRM
• ERP
• Enterprise Asset Management
• Financial Management
• Human Capital Management
• Product Lifecycle Management
• Procurement
• Supply Chain Management
• …
Big Data
• Social Media
• Website traffic
• Machine log files
• Sensor data
• Documents
• Videos, images, etc.
VOLUME
Small Data
• Megabytes (106)
• Gigabytes (109)
• Terabytes (1012)
Big Data
• Terabytes (1012)
• Petabytes (1015)
• Exabytes (1018)
• Zettabytes (1021)
VELOCITY
Small Data
• Batch
• Periodic
• Near Real-time
Big Data
• Real-time
VARIETY
Small Data
• Structured
Big Data
• Structured
• Unstructured
What matters most for your company?
Big Data or Small Data?
1. Small Data can have Big stories to tell
Analysis of NBA player
salaries
Number of rows: 11,077
File size: 402KB in XLSX
Michael Jordan
$33m
Michael Jordan
$30m
Kobe Bryant
$30m
Top Salary Earners by Year
Data Source: Patricia Bender http://www.eskimo.com/~pbender/
Software: Visart http://www.visart.io
Data Story: http://www.visart.io/degrees-of-salaries-in-the-nba/
Who is the top lifetime salary earner?
A. Michael Jordan
B. Kobe Bryant
C. Shaquille O’Neal
D. Kevin Garnett
#90
What do we know about our
presidents?
Number of rows: 43
File size: 12KB in CSV
Job security
What is the probability of getting elected to a
second term?
48.84% chance of reelection to a second term
Data Source: Wikipedia
Software: Visart http://www.visart.io
Data Story: http://www.visart.io/could-you-be-the-next-president-here-are-8-ways-to-tell/
63.16% chance of reelection to a second term
More recent history: 1900+
Data Source: Wikipedia
Software: Visart http://www.visart.io
Data Story: http://www.visart.io/could-you-be-the-next-president-here-are-8-ways-to-tell/
75% chance of reelection to a second term
More recent history: 1900+ AND Democrat
Data Source: Wikipedia
Software: Visart http://www.visart.io
Data Story: http://www.visart.io/could-you-be-the-next-president-here-are-8-ways-to-tell/
2. Data Visualization is crucial
Human brain can process visuals 60,000 times
faster than text
Data Source: Office of Travel and Tourism Industries (OTTI)
Software: Visart http://www.visart.io
Data Story: http://www.visart.io/where-do-americans-travel-the-most-abroad-2/
Data Source: Office of Travel and Tourism Industries (OTTI)
Software: Visart http://www.visart.io
Data Story: http://www.visart.io/where-do-americans-travel-the-most-abroad-2/
Data Source: CIA World Factbook 2014
Software: Visart http://www.visart.io
Data Story: http://www.visart.io/what-geographic-data-can-tell-us-about-life-expectancy/
Data Source: CIA World Factbook 2014
Software: Visart http://www.visart.io
Data Story: http://www.visart.io/what-geographic-data-can-tell-us-about-life-expectancy/
Data Visualization (DV) Tools
Self-service capabilities
Data Visualization features supported:
- Drill-down
- Geospatial visualization
- Wide variety of visual controls
Modeling and Analytics
Social Features:
- Online collaboration
- Integration with social media
Accessibility:
- Browser based
- Mobile support
Portability:
- Ease of migration (No vendor lock-in)
- Cloud and on-premise licensing
- Commodity cloud
Summary
Handle your small data first
Data Visualization is the key to understand your
data

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Big Data v. Small data - Rules to thumb for 2015

  • 1. Big Data Visualization Ugur Kadakal, PhD Founder and CEO Pagos, Inc.
  • 2. What is Big Data?
  • 3. “Big data is an all-encompassing term for any collection of data sets so large and complex that it becomes difficult to process using traditional data processing applications.” Wikipedia http://en.wikipedia.org/wiki/Big_data
  • 4. “Big data refers to datasets whose size is beyond the ability of typical database software tools to capture, store, manage, and analyze. This definition is intentionally subjective and incorporates a moving definition of how big a dataset needs to be in order to be considered big data—i.e., we don’t define big data in terms of being larger than a certain number of terabytes (thousands of gigabytes).” McKinsey http://www.mckinsey.com/insights/business_technology/big_data_ the_next_frontier_for_innovation
  • 5. “While the use of the term is quite nebulous and is often co-opted for other purposes, I’ve understood “big data” to be about analysis for data that’s really messy or where you don’t know the right questions or queries to make — analysis that can help you find patterns, anomalies, or new structures amidst otherwise chaotic or complex data points.” Philip Ashlock Chief Architect Data.gov http://datascience.berkeley.edu/what-is-big-data/
  • 6. “Historically, most decisions — political, military, business, and personal — have been made by brains [that] have unpredictable logic and operate on subjective experiential evidence. “Big data” represents a cultural shift in which more and more decisions are made by algorithms with transparent logic, operating on documented immutable evidence. I think “big” refers more to the pervasive nature of this change than to any particular amount of data.” Daniel Gillick Senior Research Scientist Google http://datascience.berkeley.edu/what-is-big-data/
  • 7. “What’s “big” in big data isn’t necessarily the size of the databases, it’s the big number of data sources we have, as digital sensors and behavior trackers migrate across the world. As we triangulate information in more ways, we will discover hitherto unknown patterns in nature and society — and pattern-making is the wellspring of new art, science, and commerce.” Quentin Hardy Deputy Tech Editor The New York Times http://datascience.berkeley.edu/what-is-big-data/
  • 8. “To me, “big data” is the situation where an organization can (arguably) say that they have access to what they need to reconstruct, understand, and model the part of the world that they care about. Using their big data, then, they can (try to) predict future states of the world, optimize their processes, and otherwise be more effective and rational in their activities” Harlan Harris Director Data Science at Education Advisory Board http://datascience.berkeley.edu/what-is-big-data/
  • 9. “The joke is that big data is data that breaks Excel, but we try not to be snooty about whether you measure your data in MBs or PBs. Data is more about your team and the results they can get.” Brian Wilt Senior Data Scientist Jawbone http://datascience.berkeley.edu/what-is-big-data/
  • 10. “You cannot give me too much data. I see big data as storytelling — whether it is through information graphics or other visual aids that explain it in a way that allows others to understand across sectors. I always push for the full scope of the data over averages and aggregations — and I like to go to the raw data because of the possibilities of things you can do with it.” Mike Cavaretta Data Scientist and Manager Ford Motor COmpany http://datascience.berkeley.edu/what-is-big-data/
  • 11. “Big data, which started as a technological innovation in distributed computing, is now a cultural movement by which we continue to discover how humanity interacts with the world — and each other — at large-scale.” Drew Conway Head of Data Project Florida http://datascience.berkeley.edu/what-is-big-data/
  • 12. “Big Data is nothing more than a tool for capturing reality — just as newspaper reporting, photography and long-form journalism are. But it’s an exciting tool, because it holds the potential of capturing reality in some clearer and more accurate ways than we have been able to do in the past” David Leonhardt Editor The Upshot, The New York Times http://datascience.berkeley.edu/what-is-big-data/
  • 13.
  • 14. BIG DATA vs SMALL DATA
  • 15. DATA SOURCES Small Data • CRM • ERP • Enterprise Asset Management • Financial Management • Human Capital Management • Product Lifecycle Management • Procurement • Supply Chain Management • … Big Data • Social Media • Website traffic • Machine log files • Sensor data • Documents • Videos, images, etc.
  • 16. VOLUME Small Data • Megabytes (106) • Gigabytes (109) • Terabytes (1012) Big Data • Terabytes (1012) • Petabytes (1015) • Exabytes (1018) • Zettabytes (1021)
  • 17. VELOCITY Small Data • Batch • Periodic • Near Real-time Big Data • Real-time
  • 18. VARIETY Small Data • Structured Big Data • Structured • Unstructured
  • 19. What matters most for your company? Big Data or Small Data?
  • 20. 1. Small Data can have Big stories to tell
  • 21. Analysis of NBA player salaries
  • 22. Number of rows: 11,077 File size: 402KB in XLSX
  • 23. Michael Jordan $33m Michael Jordan $30m Kobe Bryant $30m Top Salary Earners by Year Data Source: Patricia Bender http://www.eskimo.com/~pbender/ Software: Visart http://www.visart.io Data Story: http://www.visart.io/degrees-of-salaries-in-the-nba/
  • 24. Who is the top lifetime salary earner?
  • 25. A. Michael Jordan B. Kobe Bryant C. Shaquille O’Neal D. Kevin Garnett
  • 26.
  • 27. #90
  • 28. What do we know about our presidents?
  • 29. Number of rows: 43 File size: 12KB in CSV
  • 31. What is the probability of getting elected to a second term?
  • 32. 48.84% chance of reelection to a second term Data Source: Wikipedia Software: Visart http://www.visart.io Data Story: http://www.visart.io/could-you-be-the-next-president-here-are-8-ways-to-tell/
  • 33. 63.16% chance of reelection to a second term More recent history: 1900+ Data Source: Wikipedia Software: Visart http://www.visart.io Data Story: http://www.visart.io/could-you-be-the-next-president-here-are-8-ways-to-tell/
  • 34. 75% chance of reelection to a second term More recent history: 1900+ AND Democrat Data Source: Wikipedia Software: Visart http://www.visart.io Data Story: http://www.visart.io/could-you-be-the-next-president-here-are-8-ways-to-tell/
  • 35. 2. Data Visualization is crucial
  • 36. Human brain can process visuals 60,000 times faster than text
  • 37. Data Source: Office of Travel and Tourism Industries (OTTI) Software: Visart http://www.visart.io Data Story: http://www.visart.io/where-do-americans-travel-the-most-abroad-2/
  • 38. Data Source: Office of Travel and Tourism Industries (OTTI) Software: Visart http://www.visart.io Data Story: http://www.visart.io/where-do-americans-travel-the-most-abroad-2/
  • 39. Data Source: CIA World Factbook 2014 Software: Visart http://www.visart.io Data Story: http://www.visart.io/what-geographic-data-can-tell-us-about-life-expectancy/
  • 40. Data Source: CIA World Factbook 2014 Software: Visart http://www.visart.io Data Story: http://www.visart.io/what-geographic-data-can-tell-us-about-life-expectancy/
  • 43. Data Visualization features supported: - Drill-down - Geospatial visualization - Wide variety of visual controls
  • 44.
  • 46. Social Features: - Online collaboration - Integration with social media
  • 48. Portability: - Ease of migration (No vendor lock-in) - Cloud and on-premise licensing - Commodity cloud
  • 50. Handle your small data first
  • 51. Data Visualization is the key to understand your data

Notes de l'éditeur

  1. To understand big data we should first understand small data