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BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
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BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!

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This is a panel/workshop session developed for NEXT 2014 in Berlin. …

This is a panel/workshop session developed for NEXT 2014 in Berlin.

Guests:
Lisa Lang (Twilio) Anke Domscheit-Berg (Opengov.me) Olga Steidl (Linko ) Ivan P. Yamshchikov (Yandex) Felienne Hermans (TU Delft)

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Content:

Everyone is talking about Big Data – but what’s really behind it and how can you make data work for your business?
Collecting data is just one part of the puzzle. To source the right information, read it so it makes sense and -finally- how to execute on it is the most important task for successful big data management.
At this panel workshop we’ll listen to a lot of examples from big companies who’re dealing with massive amount of data on a daily basis. Each panel member will give a short demo and insight to their strategies and might revile some surprising facts.
This workshop is organised in cooperation with Berlin Geekettes.

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Transcript

  • 1. BIG DATA MANAGEMENT – forget the hype, let‘s talk facts A PANEL WORKSHOP POWERED BY GEEKETTES.IO
  • 2. BIG DATA MANAGEMENT – forget the hype, let‘s talk facts Ivan P. Yamshchikov Senior Analyst Yandex
  • 3. Ivan Yamshchikov, @kr0niker Senior Analyst Analytics and big data. Ecosystem.
  • 4. Yandex: >6000 employees, 9 countries and closer than you think.
  • 5. “Maths in internet analytics is like nailing something on a space ship. You might know how to use nails, yet it does not mean that you’ll do it right.” Me.
  • 6. Analytics in Yandex What does analyst do? And why does he do it?
  • 7. Analytics and big data. • Giving common sense to managers and marketing. • Giving insights to the developers.
  • 8. Why do you always need to have it? Common sense
  • 9. Do you have some common sense? How is this service doing?
  • 10. Do you have some common sense? How is this service doing?
  • 11. Do you have some common sense? How is this service doing?
  • 12. Do you have some common sense? How is this service doing?
  • 13. Do not look for answers before you have questions.
  • 14. Summing up: 1. - Analytics helps you to ask the right question. - Big data gives you the answer. 2. - Big data gives you a lot of stuff to analyze. - Analytics gives you understanding which data you actually need 3. - Big data gives you correlations. - Analytics helps to understand them.
  • 15. Ivan Yamshchikov Senior analyst @kr0niker kroniker@yandex-team.ru Thanks.
  • 16. Felienne Hermans Professor and Entrepreneur Delft University of Technology BIG DATA MANAGEMENT – forget the hype, let‘s talk facts
  • 17. Spreadsheets: The dark matter of IT Felienne Hermans Delft University of Technology
  • 18. Spreadsheets: The dark matter of IT Felienne Hermans Delft University of Technology
  • 19. Spreadsheets exist ‘under the radar’
  • 20. Spreadsheets live 5 years on average
  • 21. Average sheet is used by 12 people
  • 22. 33%
  • 23. Disaster!
  • 24. Horror stories
  • 25. Horror stories European Spreadsheet Risk Interest Group
  • 26. Horror stories European Spreadsheet Risk Interest Group
  • 27. What can we do?
  • 28. Visualize
  • 29. Visualization! Felienne Hermans (@felienne)
  • 30. BIG DATA MANAGEMENT – forget the hype, let‘s talk facts Anke Domscheit-Berg Publicist, Activist & Politican Opengove.me
  • 31. Big Government. Big Data. Anke Domscheit-Berg @anked www.opengov.me Berlin, 05.05.2014
  • 32. Big Government Data. The Good. The Bad. The Ugly. Where data can help • Health registers • Accident registers • Real time traffic data • Environmental data • Public service data • Educational data • Infrastructure data • Spending data • … -> better services, less corruption, wiser spending, life- saving Where data can be (and is) abused • Profiling of “transparent” citizens • Algorithms replace human judgement • Shared data bases – exponential power • … -> manipulation, black mailing, oppression, control, murder (drones)
  • 33. Data can be life saving (http://bluebook.scts.org/) 2005: Guardian wins legal battle to get data published on mortality rates after heart surgery
  • 34. Data can eliminate our privacy. • MIT could identify 95% of 1.5m People based on anonymised location data of their mobile phones • 4 location + time data sets of one mobile phone are sufficient to identify a person, in more complex cases, 11 data sets are needed • Comparison? 12 data sets are required for a safe identification of a human being based on his/her finger print “its only meta data”
  • 35. Freedom of Speech can vanish. “What a relief, I got an anti-flu vaccine, which only causes mild symptoms. Getting a real infection caused by the flu would have been really bad.”
  • 36. US DHS finds 377 Words suspicious
  • 37. US DHS finds 377 Words suspicious German BND uses 15.000 “suspicious” words to filter communications.
  • 38. BIG DATA MANAGEMENT – forget the hype, let‘s talk facts Olga Steidl Growth Hacker Linko
  • 39. NEXT 20 14 ! Olga St eidl ! @linkoapp ! w w w.linko.io
  • 40. Let talk about good data for sales instead… Bad Big Data is scary
  • 41. It doesn’t matter what you give away, what matters is to WHOM and WHAT YOU GET out of that. Raw Data is just RAW data.
  • 42. Big Data for Sales: Infrastructure Smart algorithms
  • 43. 1. App fragmentation 2. Personal choices are driving mobile use cases
  • 44. 40 years & golden wat ch 4 x 10 years 10 x 4 years 10 concurrent projects at all times Careers are shorter
  • 45. Morning & Afternoon One hour sessions Few minutes at a time Few seconds at a time Attention span is shorter
  • 46. 9 Evolution of Apps From hours to few moments at a time.
  • 47. @linkoapp ! w w w.linko.io
  • 48. BIG DATA MANAGEMENT – forget the hype, let‘s talk facts Thank you Ivan, Felienne, Anke, Olga Berlin Geekettes & NEXT
  • 49. European Demo Day June 6th Berlin Geekettes.io
  • 50. Thank you! Lisa Lang @lilaineuroe

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