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Big data @ #Webcoast

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A talk given at #Webcoast 2015 about big data in general and as a starting point for a discussion on the topic.

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Big data @ #Webcoast

  1. 1. Multicolour Jelly Belly beans in Sugar! by MsSaraKelly on Flickr (CC-BY) Big data Webcoast 2015 Per Olof Arnäs @Dr_PO Slides on slideshare.net/poar
  2. 2. Film by Foursquare. Google: checkins foursquare
  3. 3. Jawbone measures sleep interruption during earthquake https://jawbone.com/blog/napa-earthquake-effect-on-sleep/
  4. 4. 892 by benmschmidt on Flickr (C)19th century shipping visualized through the logs of Matthew Fontaine Maury (1806-1873), US Navy Shipping movements in the 19th century
  5. 5. So… What IS Big data?
  6. 6. 2011 2013 2015 ”Big data is an all- encompassing term for any collection of data sets so large and complex that it becomes difficult to process using on-hand data management tools or traditional data processing applications.” - Wikipedia 2015
  7. 7. Not statistics Exhausted by Adrian Sampson on Flickr (CC-BY) just
  8. 8. Not Business Intelligence Basingstoke Office Staff Desk "No computer" by John Sheldon on Flickr (CC-BY,NC,SA) just
  9. 9. http://dashburst.com/infographic/big-data-volume-variety-velocity/
  10. 10. http://www.scdigest.com/ontarget/ 14-01-21-1.php?cid=7767 Speculative shipping Package item(s) as a package for eventual shipment to a delivery address Associate unique ID with package Select destination geographic area for package Ship package to selected distribution geographic area without completely specifying delivery address Orders satisfied by item(s) received? Package redirected? Determine package location Convey delivery address, package ID to delivery location Assign delivery address to package Deliver package to delivery address Convey indication of new destination geographic area and package ID to current location Yes Yes No No smile! by Judy van der Velden (CC-BY,NC,SA)
  11. 11. 7Big Data Best Practice Across Industries Usage of data in order to: Increase Level of Transparency Optimize Resource Consumption Improve Process Quality and Performance Increase customers loyalty and retention Performing precise customer segmentation and targeting Optimize customer interaction and service Expanding revenue streams from existing products Creating new revenue streams from entirely new (data) products Exploit data for: Capitalize on data by: New Business Models Customer Experience Operational Efficiency Use data to: • Increase level of transparency • Optimize resource consumption • Improve process quality and performance Exploit data to: • Increase customer loyalty and retention • Perform precise customer segmentation and targeting • Optimize customer interaction and service Capitalize on data by: • Expanding revenue streams from existing products • Creating new revenue streams from entirely new (data) products New Business ModelsCustomer ExperienceOperational Efficiency Figure 4: Value dimensions for Big Data use cases; Source: DPDHL / Detecon DHL 2013: ”Big Data in Logistics”
  12. 12. Measure real-time system behaviour Emil Johansson - EJOH.SE
  13. 13. Collecting data - a new world emerging
  14. 14. Predict future events
  15. 15. http://blog.digital.telefonica.com/?press-release=telefonica-dynamic-insights-launches-smart-steps-in-the-uk Vizualisation
  16. 16. Created by Oliver O'Brien (UCL Geography/UCL CASA) Vizualisation
  17. 17. Locals and Tourists #1 (GTWA #2): London by Eric Fischer on Flickr Vizualisation
  18. 18. Vizualisation/combination
  19. 19. Vizualisation/combination
  20. 20. Manage complex systems Image from: http://www.as-coa.org/watchlisten/ascoa-visits-rios-operations-center
  21. 21. Avoid unpleasant surprises
  22. 22. Domain knowledge critical! See for instance: Waller, M. A. and Fawcett, S. E. (2013), Data Science, Predictive Analytics, and Big Data: A Revolution That Will Transform Supply Chain Design and Management. JOURNAL OF BUSINESS LOGISTICS, 34: 77–84 Data scientists - the new superstars "Data Science Venn Diagram" by Drew Conway - Own work. Licensed under Creative Commons Attribution- Share Alike 3.0 via Wikimedia Commons - http://commons.wikimedia.org/wiki/ File:Data_Science_Venn_Diagram.png#mediaviewer/File:Data_Science_Venn_Diagram.png
  23. 23. Challenges The Challenger by Martín Vinacur on Flickr (CC-BY) Cross-disciplinary Cross-industries Cross-borders
  24. 24. Multicolour Jelly Belly beans in Sugar! by MsSaraKelly on Flickr (CC-BY) Big data Webcoast 2015 Per Olof Arnäs @Dr_PO Slides on slideshare.net/poar

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