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Big Data: how to use it to create value

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Every body talks about Big Data, but why? Do it create value? Do it enable some paradigmatic shifts in the way we work with data? This talk I did at ComoNext research and technological park cast some light on those questions.

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Big Data: how to use it to create value

  1. 1. Big Data: how to use it to create value Emanuele Della Valle @manudellavalle h9p://emanueledellavalle.org
  2. 2. Agenda •  Why now? •  Its value •  What is it? •  Paradigm shiCs enabled 11/01/2017 @manudellavalle - h9p://emanueledellavalle.org 2
  3. 3. Why now? 1/3 11/01/2017 @manudellavalle - h9p://emanueledellavalle.org 3
  4. 4. Why now? 2/3 [source: h9p://www.intel.com/newsroom/bigdata/] 11/01/2017 @manudellavalle - h9p://emanueledellavalle.org 4
  5. 5. Why now? 3/3 11/01/2017 @manudellavalle - h9p://emanueledellavalle.org 5 1 TB : = 1 ZB : the great wall
  6. 6. Its value 1/4 11/01/2017 @manudellavalle - h9p://emanueledellavalle.org 6
  7. 7. Its value 2/4 [source: McKinsey, 2011] 11/01/2017 @manudellavalle - h9p://emanueledellavalle.org 7 healthcare Public AdministraTons Personal locaTon
  8. 8. Its value 3/4 [source: McKinsey, 2011] 11/01/2017 @manudellavalle - h9p://emanueledellavalle.org 8 margin jobs skills
  9. 9. Its value 4/4 11/01/2017 @manudellavalle - h9p://emanueledellavalle.org 9 [source: McKinsey, 2016]
  10. 10. Wrapping up … a widening gap 11/01/2017 @manudellavalle - h9p://emanueledellavalle.org 10 Intensity 90's 2000's 2010's 2020's Data Availability Execution Capability Analytical Capability Widening Gap
  11. 11. … so what's Big Data? [source: IBM, 2012] Analysis of the answers of 1144 responders from organizaTons that run Big Data projects 11/01/2017 @manudellavalle - h9p://emanueledellavalle.org 11
  12. 12. CharacterisTcs 1/5 [source: IBM, 2012] 11/01/2017 @manudellavalle - h9p://emanueledellavalle.org 12
  13. 13. CharacterisTcs 2/5 [source: IBM, 2012] 11/01/2017 @manudellavalle - h9p://emanueledellavalle.org 13
  14. 14. CharacterisTcs 3/5 [source: IBM, 2012] 11/01/2017 @manudellavalle - h9p://emanueledellavalle.org 14
  15. 15. CharacterisTcs 4/5 [source: IBM, 2012] the one certainty about uncertainty is that it is not likely to go away 11/01/2017 @manudellavalle - h9p://emanueledellavalle.org 15
  16. 16. CharacterisTcs 5/5 [source: IBM, 2012] 11/01/2017 @manudellavalle - h9p://emanueledellavalle.org 16
  17. 17. Paradigm ShiCs Enabled 1/4 [source: Marc Andrews, 2014] Leverage more of the data being captured 11/01/2017 @manudellavalle - h9p://emanueledellavalle.org 17
  18. 18. Paradigm ShiCs Enabled 1/4 [source: Marc Andrews, 2014] Leverage more of the data being captured 11/01/2017 @manudellavalle - h9p://emanueledellavalle.org 18
  19. 19. Paradigm ShiCs Enabled 1/4 11/01/2017 @manudellavalle - h9p://emanueledellavalle.org 19
  20. 20. Paradigm ShiCs Enabled 2/4 11/01/2017 @manudellavalle - h9p://emanueledellavalle.org 20 Reduce effort required to leverage data [source: Marc Andrews, 2014]
  21. 21. Paradigm ShiCs Enabled 2/4 11/01/2017 @manudellavalle - h9p://emanueledellavalle.org 21 Reduce effort required to leverage data [source: Marc Andrews, 2014]
  22. 22. Happily inside a bo9le of Heineken beer @ the Heineken Magazzini #heinekendesignweek Event Milan Design Week Event Heineken Design Week Loca*on The Magazzini hosts has loca)on J Paradigm ShiCs Enabled 2/4 Knowledge Graph W Company Heineken W Drink beer produces organized by Wide as open data As deep as your DB can make it Example of reduce effort required to leverage data 11/01/2017 @manudellavalle - h9p://emanueledellavalle.org 22
  23. 23. Paradigm ShiCs Enabled 2/4 Coca cola Parinne 11/01/2017 @manudellavalle - h9p://emanueledellavalle.org 23 Another example of reduce effort required to leverage data
  24. 24. Paradigm ShiCs Enabled 3/4 Data-driven exploraTon looking for correlaTon 11/01/2017 @manudellavalle - h9p://emanueledellavalle.org 24 [source: Marc Andrews, 2014]
  25. 25. Paradigm ShiCs Enabled 3/4 Data-driven exploraTon looking for correlaTon 11/01/2017 @manudellavalle - h9p://emanueledellavalle.org 25 [source: Marc Andrews, 2014]
  26. 26. Paradigm ShiCs Enabled 3/4 When the series House of Cards began shopping around for a home, Ne:lix aggressively jumped on it, outbidding major cable networks with a massive two-season order. 28/09/2016 @manudellavalle - h9p://emanueledellavalle.org 26 Example of Data-driven exploraTon looking for correlaTon
  27. 27. •  By analyzing its data, Nejlix saw that a large majority of its viewers enjoy programs : –  directed by David Fincher (who directed Se7en, Fight Club and The Social Network) –  starring Kevin Spacey. •  House of Cards was exactly that! 28/09/2016 @manudellavalle - h9p://emanueledellavalle.org 27 Paradigm ShiCs Enabled 3/4 Example of Data-driven exploraTon looking for correlaTon
  28. 28. Paradigm ShiCs Enabled 4/4 Leverage data as it is captured 11/01/2017 @manudellavalle - h9p://emanueledellavalle.org 28 [source: Marc Andrews, 2014]
  29. 29. Paradigm ShiCs Enabled 4/4 Leverage data as it is captured 11/01/2017 @manudellavalle - h9p://emanueledellavalle.org 29 [source: Marc Andrews, 2014]
  30. 30. Paradigm ShiCs Enabled 4/4 11/01/2017 @manudellavalle - h9p://emanueledellavalle.org 30
  31. 31. Wrapping up … the "Data Lake" 11/01/2017 @manudellavalle - h9p://emanueledellavalle.org 31 [source: h9ps://soluTonsreview.com/data-integraTon/the-emergence-of-data-lake-pros-and-cons/ ]
  32. 32. Wrapping up … the "Data Lake" 11/01/2017 @manudellavalle - h9p://emanueledellavalle.org 32 [source: h9ps://twi9er.com/CamSemanTcs/status/815273814087127041 ]
  33. 33. Credits •  Big Data: the next fronTer for innovaTon, compeTTon, and producTvity. McKinsey Global InsTtute. May, 2011. –  h9p://www.mckinsey.com/insights/business_technology/big_data_the_next_fronTer_for_innovaTon •  AnalyTcs: The real-world use of big data. IBM InsTtute for Business Value In collaboraTon with Saïd Business School at the University of Oxford. 2012 –  h9p://www-03.ibm.com/systems/hu/resources/the_real_word_use_of_big_data.pd •  Big Data & AnalyTcs: Next GeneraTon Architecture and CapabiliTes. Marc Andrews, 2014 –  h9ps://www.ibm.com/partnerworld/wps/servlet/RedirectServlet?cmsId=isv_ast_smp_ecosystem- webcasts&a9achmentName=Data_Warehouse_deck.pdf •  Big Data for Media. Martha L. Stone. REUTERS INSTITUTE for the STUDY of JOURNALISM, Oxford University, 2014 –  9p://reutersinsTtute.poliTcs.ox.ac.uk/publicaTon/big-data-media •  Wimbledon fans love real-Tme analyTcs. IBM AnalyTcs, 2015 –  h9p://www.ibmbigdatahub.com/presentaTon/wimbledon-fans-love-real-Tme-analyTcs •  The Age Of AnalyTcs: CompeTng In A Data-driven World. McKinsey, 2016 –  h9p://www.mckinsey.com/business-funcTons/mckinsey-analyTcs/our-insights/the-age-of- analyTcs-compeTng-in-a-data-driven-world 11/01/2017 @manudellavalle - h9p://emanueledellavalle.org 33
  34. 34. Thank you! Any QuesTon? Emanuele Della Valle @manudellavalle h9p://emanueledellavalle.org

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