Big Data e as Tecnologias Disruptivas - TDC 2014

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Big Data e as Tecnologias Disruptivas - TDC 2014

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Big Data e as Tecnologias Disruptivas - TDC 2014

  1. 1. Big Data e as Tecnologias Disruptivas José Papo @josepapo
  2. 2. “Algorithms have already written symphonies as moving as those composed by Beethoven, picked through legalese with the deftness of a senior law partner, diagnosed patients with more accuracy than a doctor, written news articles like a seasoned reporter, and driven vehicles on urban highways with better control than a human driver.” !
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  4. 4. Collect/Supply: Gather and sell raw data. Interested parties will pay you so they don’t have to gather the data on their own.
  5. 5. Store/Host: Provide a way to hold on to someone else’s data for them. This can be especially profitable if you hold the same data for several parties, as you benefit from economies of scale.
  6. 6. Filter/Refine: Data cleansing is a thankless but necessary task in any analytics exercise. Instead of just selling someone a raw dataset, you can charge a premium for one that omits duplicate records and otherwise dirty data.
  7. 7. Enhance/Enrich: Add value to a raw dataset by merging it with another, or by precomputing results that people are likely to use.
  8. 8. Simplify Access: Help people cherry-pick the data they want, in the format they prefer. This can be as simple as converting data to a more convenient format (say, from PDF to CSV), to something as complex as a system that helps people find data and subset it to their liking.
  9. 9. Analyze: Uncover new information to guide business decisions, and otherwise explore data to answer questions.
  10. 10. Obscure: Data has become easier to collect over the years, but not everyone wishes to be part of an analytics exercise. Certain businesses make their money by helping people and businesses keep their data from prying eyes.
  11. 11. Consult/Advise: Data has become a key ingredient in a number of business realms. Specialized consultants can help firms to make the most of their data, from how to analyze it to how to monetize it.
  12. 12. Agricultura ○○○○
  13. 13. Manufatura e Equipamentos ○○○○
  14. 14. « Os novos times de inovação serão compostos por cientistas de dados, desenvolvedores de software, especialistas em Cloud e projetistas industriais/hardware» Tim O’Reilly
  15. 15. Publicidade e Retail ○○○○
  16. 16. Finanças ○○○○
  17. 17. Saúde ○○○○
  18. 18. Educação ○○○○
  19. 19. Transporte ○○○○
  20. 20. Turismo e Hotelaria ○○○○
  21. 21. OBRIGADO!! ! slideshare.net/jpapo

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