Big Data and Analytics - 2016 CFO
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- 3. Big Data and the Future of Analytics Presented by: John-Paul Della Putta
- 4. Our Agenda for Today Evolving Analytics From 1.0 to 3.0 4 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
- 5. Evolving Analytics Analytics 1.0 to 3.0
- 7. 7 From Analytics 1.0 to 3.0
- 8. Analytics 1.0 Good old fashioned reporting & BI 8 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
- 9. Analytics 2.0 The Rise of Big Data 9 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
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- 11. Analytics 3.0 Closing the loop 11 = Traditional Analytics + Big Data Technology + (possibly Big Data) + Prescribed Action
- 12. Example – Remote Gas Well Maintenance What action will be taken automatically? 12
- 13. Lower Costs 13 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
- 14. How operational analytics ‘operate’
- 15. It’s not analytics for operations
- 16. 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
- 17. Recommended for You An example of operational analytics 17 Redshift is Amazon’s Hadoop as a service
- 18. Internet Of Thing Be careful – lots of noise, not much signal 18
- 19. Mini Crash The Dark Side of Operational Analytics 19
- 20. Google Flu-trends Over-states actual flu incidents by 50% 20
- 21. Big Data Some real world examples
- 23. Siri was a pentagon labs experiment Uses big data and machine learning etc. 23
- 24. Recommendation Engines 24 Average of many algorithms
- 25. Where Big Data is Used 25 Recommendations Risk, Fraud & Security Marketing
- 26. Better decisions 5 – 6% INCREASE
- 27. Big Data 101 A crash course
- 28. Not Your Usual Data Big data’s not just big – it’s different 28 Different Data Big Data is exciting because of all the new information it contains
- 29. 3+ V’s 29 Volume Velocity Variety
- 30. Instant Web Data How many Tweets / second? 30
- 32. The Irony of Big Data The Questions are Simple 32 Is this person a good credit risk? Is this movie worth watching? Is this too much to pay for this property?
- 33. Hadoop 101
- 34. Hadoop Key attributes 34 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)
- 35. It’s pretty complex.. Sorry, I wish it wasn’t, but it is… 35
- 36. Better Decisions 36 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
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- 39. How do You as a CFO Use Big Data? Will you be deploying your own Hadoop Cluster? 39
- 40. Renting Data Not ready to build your own Hadoop cluster? 40
- 41. Qlik Data Market
- 43. The Way to a Man’s Heart is Through his Stomach The Way to a CFO’s Heart, is Through Their Budget 43
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- 45. "Information is the oil of the 21st century, and analytics is the combustion engine” (Peter Sondergaard, Senior Vice President, Gartner)
- 46. End users want to be able to quickly analyse their own data CFO’s don’t wait for IT
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- 52. 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
- 53. Back to the real world
- 54. Introducing KPI Pulse Or Analytics 2.5 54
- 56. KPI’s on anyone’s mobile phone No need to login to the server or have a Qlik license
- 57. Click to drill down to the details See key details and reports PDF / Excel reports
- 58. Chat between users Managers can ask why performance metrics aren’t met
- 59. Summary & Recap What we learnt
- 60. So what did you learn? 60 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
- 61. We started with science fiction
Editor's Notes
- #3: Minority Report
- #30: The techo’s will say that there’s more than just 3 V’s, which is true, but knowing these 3V’s is an excellent starting point.
- #37: MIT did a study on how data-driven-decision based businesses performed compared to standard businesses . Much of the information was from Andrew McAfee – he’s got some good information about how technology is changing business.
- #39: Zest Finance
- #46: http://www.informationweek.com/big-data/big-data-analytics/big-data-predictions-for-2016/d/d-id/1323671?image_number=4
- #47: http://www.informationweek.com/big-data/big-data-analytics/big-data-predictions-for-2016/d/d-id/1323671?image_number=4
- #56: Where it came from – A project manager using QlikView said to me, I don’t want to analyse the data – I just want to know where there’s a problem or who I should call.