Unexperienced pasts

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파일 사이즈 때문에 몇몇 페이지는 생략함.

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Unexperienced pasts

  1. 1. unexperienced Jeong, Buhwan
  2. 2. Past Present and Future 2010, & 3 yrs later
  3. 3. ~2010
  4. 4. Competition ContextControl Cloud
  5. 5. Consumption CrowdsConvenience Connection
  6. 6. 2013~
  7. 7. Curation
  8. 8. We purchase convenience.
  9. 9. Container
  10. 10. I want to travel Jeju, too.
  11. 11. Content is king.Context is anther content.
  12. 12. NEXT? Media is message.Is container the next?
  13. 13. Content Context Container TopicContents Perspective Style/Nuance Container is brand. Situation Time & SpaceContext Relation Person History/Interest ExpertiseContainer Reputation Influence
  14. 14. What do people think about us? Container is the first.
  15. 15. Culture
  16. 16. Cultural Creativity vs Creative Culture
  17. 17. Daum Culture?
  18. 18. Data-driven execution
  19. 19. Community of Practice (CoP) Spotify
  20. 20. DevDay/Hackertone Imagine impossible, do possible.
  21. 21. THEN NOW Context Container 5 Internet TrendsCompetition Convolution 1. Structured/Linked Data Control (un-)Certainty 2. Real-time Internet Cloud C 3. Personalization Crowds Curation 4. Mobile & Augmented RealityConsumption CultureConvenience Control 5. Internet of ThingsConnection Continuity ir ls? o tg h are here w
  22. 22. Data Science
  23. 23. We’ve faced challenges to dealing with Large-Scale Data Time-Series Data in Real-Time + Big Data Unstructured Data Persuasion with Interpretation & Visualization
  24. 24. Big Data Volume Platform Problem Variety o rk Velocity W + a ta D Value People Productivity PlatformMonitoring/ Decision Execution Sensing Making Intelligent System
  25. 25. Smart Data- Moving from big data to smart data- 2013: The year of smart data- Big data spotlight: Big data is dead! Long live smart data!- Big data won’t save pharma, but smart data might So Much Data, So Little Impact.- Big data? Try smart data- Investing in big data’s second act
  26. 26. Make Big Data work. Big Data + Analytics + Visualization Actionable Insight
  27. 27. If you can predict the future, you also change it.Predictive Analytics
  28. 28. Prediction Model EvaluationModel Predictive Control
  29. 29. Realtime - Simple algorithms Counting / Random Forest / Regression Accurate vs Real-time - Feature selection & summary - Streaming processing and analytics - In-memory storageData Science = Data + Analytics + Action
  30. 30. So, what?Those who cannot remember the past are condemned to repeat it. We live in pasts we’ve never lived.
  31. 31. No prepare, just repair. Make you survive by yourself.

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