2. Who am I?
@philsimon 2
• Award-winning author of six
books
• Speaker, consultant, and
technology expert
• Huge Breaking Bad fan (more
on that later)
4. Netflix Stats
• Roughly 40M customers
• Nearly $27B market cap
• Responsible for nearly one-third of all US
weeknight Internet traffic
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Data as of March 3, 2014
5. Netflix Facts
• Single biggest AWS customer
– 2012 Christmas day outage
• In September of 2013, Netflix became the first
non-TV network to win an Emmy for House of
Cards
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7. The Netflix Data Credo - 1
• Data should be accessible, easy to discover,
and easy to process for everyone.
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Source: Netflix - tinyurl.com/tvo-netflix
8. 77,000 Subgenres of Movies
• Dark Suspenseful Sci-Fi Horror Movies
• Gritty Suspenseful Revenge Westerns
• Romantic Indian Crime Dramas
• Evil Kid Horror Movies
• Visually-striking Goofy Action & Adventure
• Violent Suspenseful Action & Adventure from the 1980s
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9. The Netflix Data Credo - 2
• The longer you take to find the data, the less
valuable it becomes.
@philsimon 9
11. Stats
50,000 Netflix subscribers watched
all 13 episodes of Breaking Bad
Season 4 on the day before
Season 5 premiered.
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Source: The Hollywood Reporter
12. The Netflix Data Credo - 3
• Whether a dataset is large or small, being able
to visualize it makes it easier to explain.
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17. What does Netflix know about each of its
40M streaming customers?
• What they watch
• When they watch
• The device on which they’re watching
• When they pause and/or resume watching
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18. • He with the most data doesn’t win.
• In an era of Big Data, success hinges on what
an organization does with that information.
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19. Story Behind the Book
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How do we make sense of all of this data?
23. @philsimon 23
• The visual consumer
• The visual employee
• The visual government
• The visual citizen
• The visual journalist
• The visual athlete
It’s not just organizations…
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32. Characteristics of a Visual Organization
• Eschew “set it and forget it”
• Encourage data exploration and discovery
• Recognize the limitations of reporting
stalwarts
• Buy and build new tools as necessary
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33. Dataviz Myths
• We must visualize all of the data
• Only visualize good data
• Visualization will always manifest the right
action or decision
• Visualization leads to certainty
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34. Lessons from the book
• UX: participation and
experimentation are
paramount
• Walk before you run
• Avoid the quarterly
visualization mentality
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35. Lessons from the book
• Transparency is becoming
increasingly important
• All data is not required to
begin
• Iterate
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