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  • 1. Extracting Valuefrom Big Data in the Cloud - Michael Newberry
  • 2. Big data in a Hybrid-Cloud world Dr Michael Newberry Windows Azure Lead, Microsoft UK Michael.Newberry@Microsoft.com
  • 3. Doggerland: Simon Fitch, Vince Gaffney and Ken ThomsonImage Source: drowned-landscapes.tumblr.comRoyal Societys Summer Science Blog (http://summer-science.tumblr.com/)
  • 4. Big Data.
  • 5. VOLUME VARIETY VELOCITY (Size) (Structure) (Speed) Big Data.
  • 6. Getting useful insightsfrom awkward data setsusing the most appropriatecomputing platform at eachstage. Dr Michael Newberry Windows Azure Lead Microsoft UK
  • 7. Big data in a Hybrid-Cloud world Dr Michael Newberry Windows Azure Lead, Microsoft UK Michael.Newberry@Microsoft.com
  • 8. Machine Learning & Bayes theorem
  • 9. .Amazon (AMZN) calls this homegrown math "item-to-item collaborative filtering," and its used this algorithm to heavilycustomize the browsing experience for returning customers. Judging by Amazons success, the recommendationsystem works. The company reported a 29% sales increase to $12.83 billion during its second fiscal quarter, up from$9.9 billion during the same time last year. A lot of that growth arguably has to do with the way Amazon has integratedrecommendations into nearly every part of the purchasing process from product discovery to checkout.http://tech.fortune.cnn.com/2012/07/30/amazon-5/
  • 10. In theory there is no difference between theory and practice; in practice, there is. Yogi Berra, cited in Nassim Taleb, Antifragile.
  • 11. Big data techniquesNoSQL (ala MongoDB) Map-Reduce (e.g. Hadoop)
  • 12. Embedded devices
  • 13. Cloud OS
  • 14. MICROSOFTCloud OS 1 CONSISTENT PLATFORMON-PREMISES SERVICE PROVIDER
  • 15. MANAGE ANY DATA, ANY SIZE, ANYWHERE 010101010101010101 1010101010101010 01010101010101 101010101010
  • 16. POLYBASE: COMBINING RELATIONAL AND NON-RELATIONAL DATAThe future of query processing
  • 17. 19
  • 18. 20
  • 19. Lock-InWindows Azure Other Service Providers Windows Virtual Machine Customer Data Center
  • 20. DATA PLATFORM DELIVERY MODELSRationalefor Usage On-Premises On-Premises or Microsoft Cloud orLocation Service Provider Service Provider
  • 21. BALANCING ON PREMISE & CLOUDSnowline graph
  • 22. A
  • 23. Takeaways1. big data can do some amazing stuff.2. Dont think big data as much as data needing non- relational approaches3. If your big data insights are probabilistic, which they often are, have a plan to deal with variance.4. Pick the most appropriate platform: Think and not or: - Balance public cloud AND on-premise, - Combine big data with RDBMS.

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