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Big Data and the Future of Analytics - 2016 CFO Series


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Presentation on Big Data and the Future of Analytics from the 2016 CFO Symposium in Adelaide, Australia

Published in: Data & Analytics
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Big Data and the Future of Analytics - 2016 CFO Series

  1. 1. Big Data and the Future of Analytics Presented by: John-Paul Della Putta
  2. 2. Our Agenda for Today Evolving Analytics From 1.0 to 3.0 3 The Rise of Big Data What it is, how it can benefit you Big Data Technology What it is, what you need to know Using Big Data & Analytics? Becoming analytics driven Enhancing your Analytics Introducing KPI Pulse The Future Some Predictions
  3. 3. Evolving Analytics Analytics 1.0 to 3.0
  4. 4. 5 Analytics has Changed
  5. 5. 6 From Analytics 1.0 to 3.0
  6. 6. Analytics 1.0 Good old fashioned reporting & BI 7  Descriptive analytics  Generally backward facing and showing what’s happened and why  Often there’s a considerable lag between event and insight  Traditional BI and Reporting – still relevant today and won’t be going away soon
  7. 7. Analytics 2.0 The Rise of Big Data 8 Looking at much larger, broader data sets, often un-structured data Emergence of new technologies which deal with large volumes of often un structured data Rise of the Data Scientist
  8. 8. 9 111866146X.html Video is half way down the page
  9. 9. Analytics 3.0 Closing the loop 10 = Traditional Analytics + Big Data Technology + (possibly Big Data) + Prescribed Action
  10. 10. Example – Remote Gas Well Maintenance What action will be taken automatically? 11
  11. 11. Lower Costs 12  Railroad sensor notices that a wheel is too hot and sends a signal to stop the train  A team is sent to perform repairs  Possible derailment is avoided
  12. 12. How operational analytics ‘operate’
  13. 13. It’s not analytics for operations
  14. 14. Descriptive Summarise and describe what’s happened in the past Predictive Predict what’s likely to happen in the future Prescriptive Determine actions to take and make the future happen
  15. 15. Recommended for You An example of operational analytics 16 Redshift is Amazon’s Hadoop as a service
  16. 16. Internet Of Thing Be careful – lots of noise, not much signal 17
  17. 17. Mini Crash The Dark Side of Operational Analytics 18
  18. 18. Google Flu-trends Over-states actual flu incidents by 50% 19
  19. 19. Big Data Some real world examples
  20. 20. 21
  21. 21. Siri was a pentagon labs experiment Uses big data and machine learning etc. 22
  22. 22. Recommendation Engines 23 Average of many algorithms
  23. 23. Where Big Data is Used 24 Recommendations Risk, Fraud & Security Marketing
  24. 24. pping-habits.html?pagewanted=all&_r=3& Target Video
  25. 25. Big Data 101 A crash course
  26. 26. Not Your Usual Data Big data’s not just big – it’s different 27 Different Data Big Data is exciting because of all the new information it contains
  27. 27. 3+ V’s 28 Volume Velocity Variety
  28. 28. Instant Web Data How many Tweets / second? 29
  29. 29. Unstructured Data E.g. Emails 30
  30. 30. The Irony of Big Data The Questions are Simple 31 Is this person a good credit risk? Is this movie worth watching? Is this too much to pay for this property?
  31. 31. Hadoop 101
  32. 32. Hadoop Key attributes 33 Open source (cost effective) Stores data in 3 places (no backup) Not a database, a file system (no loading) Suitable for large amounts of unstructured data Scalable – Can be distributed over many computers (Yahoo has a 42,000 node implementation)
  33. 33. It’s pretty complex.. Sorry, I wish it wasn’t, but it is… 34
  34. 34. Better Decisions 35 Performance and market value. We find that DDD is associated with a 5 – 6% increase in their output and productivity, beyond what can be explained by traditional inputs and IT 5 – 6% Increase
  35. 35. Lowering Credit Risk
  36. 36. ZestFinance Video on Payday lending 37
  37. 37. How do You as a CFO Use Big Data? Will you be deploying your own Hadoop Cluster? 38
  38. 38. Renting Data Not ready to build your own Hadoop cluster? 39
  39. 39. Qlik DataMarket
  40. 40. Qlik DataMarket Using big data from the cloud
  41. 41. The Way to a Man’s Heart is Through his Stomach The Way to a CFO’s Heart, is Through Their Budget 42
  42. 42. 43
  43. 43. "Information is the oil of the 21st century, and analytics is the combustion engine” (Peter Sondergaard, Senior Vice President, Gartner)
  44. 44. End users want to be able to quickly analyse their own data CFO’s don’t wait for IT
  45. 45. Qlik User-driven Analytics
  46. 46. User Driven Analytics Using Qlik Sense 47 bff-5f74-403f-864c-f5e9d2d68f03
  47. 47. 48 In-Memory Instant Insights
  48. 48. Not Big-Data Good old-fashioned human research Is Yelp paying too little? Are they being too greedy? I Don’t know – need more data
  49. 49. Back to the real world
  50. 50. Introducing KPI Pulse Or Analytics 2.5  53
  51. 51. KPI’s on anyone’s mobile phone No need to login to the server or have a Qlik license
  52. 52. Click to drill down to the details See key details and reports PDF / Excel reports
  53. 53. Chat between users Managers can ask why performance metrics aren’t met
  54. 54. Summary & Recap What we learnt
  55. 55. So what did you learn? 59 If you were paying attention… Analytics is changing Moving from descriptive analytics through Predictive to Prescriptive. Big Data has 3V’s Big Data is different data and It’s being used everywhere. You might end up renting it. KPI Pulse You can get real time analytics pushed out to your users’ mobile phones Hadoop isn’t a DB It’s not a database, it’s a filesystem and it’s complex. You can use it without building it
  56. 56. We started with science fiction
  57. 57. Real life – how to catch a serial killer 2011 QlikView is used to help catch a serial killer in Sweeden