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Data Culture Keynote and Exec Track Birm Dec 8th

Business today is starting to understand the value of data, and some organisations are outperforming their competition by putting data at the heart of their thinking. Leveraging data to change business models, understand their customers and employees better and deliver new revenue streams is the driving force in this new data centric era.
Jon Woodward - MSFT
Dave Coplin - MSFT
Mike Bugembe - JustGiving
Gary Richardson - KPMG

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Data Culture Keynote and Exec Track Birm Dec 8th

  1. 1. DATA CULTUREKeynote + Exec Track Birmingham 8th December 2015
  2. 2. UK Business Lead for BI & Analytics Jon Woodward : Connect & Follow @JLWoodward www.linkedin.com/in/jonathanwoodward #DataCulture
  3. 3. Data Culture Industry Immersions Community Other Summits Events Events Sept, London 22nd Sept Data Culture Summit – Business 23rd Sept Data Culture Summit - Technical 22nd Sept Data Culture Dinner - Executives Dec, Birmingham 8th Dec Data Culture Summit, Business 9th Dec Data Culture Summit, Technical 8th Dec Data Culture Dinner, Executive March, London 8th Mar Data Culture Summit, Business 9th Mar Data Culture Summit, Technical 8th Mar Data Culture Dinner, Executive May, London 9th May Data Culture Summit, Business 10th May Data Culture Summit, Technical 9th May Data Culture Dinner, Executive Future Decoded, Nov 10-11th, London Data Culture Tracks https://futuredecoded.microsoft.com/ 10th Nov, Futures Data Platform Roundtable 10th Nov, Dashboard in an Hour 10th Nov, Data Culture Panel 10th Nov, Data Culture Dinner Gartner BI Summit , Feb 29th-1st March, London http://www.gartner.com/events/emea/busin ess-intelligence 29th Feb, Data Culture Dinner 6th October, Reading Dashboard in a Day 27th October, Reading Platform Modernisation 20th January, London Dashboard in a Day Platform Modernisation 11th February, Reading Dashboard in a Day Platform Modernisation 21st March, London Dashboard in a Day Platform Modernisation 21st April, Edinburgh Dashboard in a Day Platform Modernisation 11th May, Reading Dashboard in a Day Platform Modernisation 8th June, London Dashboard in a Day Platform Modernisation 10/11th September Cambridge SQL Saturday http://www.sqlsaturday.com/41 1/eventhome.aspx October SQL Relay http://www.sqlrelay.co.uk/ 7th Nottingham 8th London 12th Reading 13th Bristol 14th Cardiff 15th Birmingham 28th Nov, London Data Culture PowerBI Edition http://www.eventbrite.com/e/d ata-culture-day-london-power- bi-edition-tickets-18258788528 5th Nov, London IRM Data Science Track http://www.irmuk.co.uk/ed bi2015/postworkshops.cfm UK DATA CULTURE EVENTS 26th Nov, London Dashboard in a Day Platform Modernisation Cloud RoadShow, Feb 29th-1st March, London SQLSaturday, Exeter – 11/12 March SQLBits, May SQL Saturday, Edinburgh – 10/11 June
  4. 4. Data Culture for Marketing Data Culture Summits – Sept/Dec/Mar/May Data Culture for IT Executives Data Platform Modernisation Data Culture for Finance IoT Track Machine Learning and Analytics Track Visualisation and Data Discovery Track Big Data and Data Management Track Day 1 - Business Day Day 2 - Technical Day Dashboard in a Day
  5. 5. Dave Coplin – Chief Envisioning Officer, Microsoft 09.30 – 10.00 Mike Bugembe – Chief Data Officer, JustGiving Break 10.15 – 12.30 Morning Tracks Lunch 13.30 – 16.30 Dashboard in a Day Continues Close
  6. 6. Empowering the Future of Work
  7. 7. BOLDLY GO…
  8. 8. “Why work isn’t working and what you can do about it.” PREVIOUSLY…
  9. 9. “How to outsmart the digital deluge” OUT NOW….
  10. 10. WHICH IS GREENER?
  11. 11. Source: Henderson, Bobby (2005). "Open Letter To Kansas School Board". Venganza.org. Archived from the original on 2007-04-07.
  12. 12. THE POWER OF MACHINE LEARNING
  13. 13. "Aoccdrnig to a rseecharer at Cmabrigde Uinervtisy, it deosn't mttaer in waht oredr the ltteers in a wrod are, the olny iprmoatnt tihng is taht the frist and lsat ltteers be at the rghit pclae. The rset can be a toatl mses and you can sitll raed it wouthit porbelm. Tihs is bcuseae the huamn mnid deos not raed ervey lteter by istlef, but the wrod as a wlohe."
  14. 14. A QUESTION OF TRUST
  15. 15. Image copyright: CBS Studios Inc.
  16. 16. REMEMBER, COMPUTERS ARE USELESS…
  17. 17. 40
  18. 18. No good cause should go unfunded
  19. 19. 43b 16 5 Countrie s 25m Users $3b n Raised 10 Currencie s
  20. 20. The Predictability Discovery and Engagement
  21. 21. A recommendation engine to suggest content
  22. 22. Personalisation
  23. 23. Traditional methods don’t work in this space
  24. 24. Lots of research and working with academics
  25. 25. Its about social relationships and networks
  26. 26. The answer was staring us in the face every day
  27. 27. We live in a connected world
  28. 28. People supporting others
  29. 29. 87million nodes
  30. 30. 420million relationships
  31. 31. We can run calculations over these networks
  32. 32. So this is what we planned to build 14 years of giving behaviour, online, web traffic, academic research Engagin g Machine Learning Social Graph Theory Personal
  33. 33. To achieve our vision we built an intelligent machine that… Give Care about Engaging content
  34. 34. Building a real-time graph is hard!
  35. 35. SecureFlexibility Always up always on Platform as a service
  36. 36. HDInsight Azure Cloud Services Azure Service Bus Azure Table Storage F# Azure websites (with Auto scaling & Storage Queues)
  37. 37. Microsoft Azure SQL Database Importer Service Service BusBlob Storage Website Redis Cache Table Storage WebsiteHDInsight F# Mailbox
  38. 38. No good cause should go unfunded
  39. 39. mike.bugembe@justgiving.com mike@CAOtoday.com @mikeBugembe https://uk.linkedin.com/in/mikebugembe
  40. 40. #DataCulture Microsoft Data Culture - UK
  41. 41. Intro + Welcome 10.30 – 11.00 Benefits of a Data Culture 11.00 – 11.45 The Future is Data Driven 11.45 – 12.15 Enabling Data Culture in your Organisation 12.15 – 12.30 Next Steps Lunch
  42. 42. UK Business Lead for BI & Analytics Jon Woodward : Connect & Follow @JLWoodward www.linkedin.com/in/jonathanwoodward #DataCulture
  43. 43. Director of Data Engineering, KPMG Gary Richardson: Connect & Follow @GaryData https://uk.linkedin.com/in/richardsongary
  44. 44. Introductions
  45. 45. #DataCulture Microsoft Data Culture - UK
  46. 46. What differentiates today’s thriving organizations? Data. #DataCulture
  47. 47. www.slideshare.net/jonathanwoodward1 Algorithm’s Things Intelligence
  48. 48. Algorithm’s • Predicating next best outcome • Finding patterns • Uncovering Anomalies Yesterday
  49. 49. Algorithm’sThings 25 billion Connected “things” by 2020 —Gartner $1.7 trillion Market for IoT by 2020 —IDC Today
  50. 50. Algorithm’sThings • Create new business models • Provide better service and improve customer experiences • Respond to changes in the market faster • Improve product availability and usage • Open new revenue streams
  51. 51. Algorithm’sIntelligence Predictions – Ray Kurzweil 2010- Supercomputer to emulate human intelligence 2020 – Human intelligence computing available for $1000 2029 – Pass Turing Test 2030 – non-biological computation will surpass capacity of all living human intelligence 2045 – Singularity Tomorrow
  52. 52. Algorithm’sIntelligence • Creating Intelligent Applications • Creating more personal experiences • Connecting Algorithms and Things
  53. 53. #DataCulture How will YOU differentiate YOUR organization?
  54. 54. #DataCulture Microsoft Data Culture - UK
  55. 55. DATA SCIENCE&ENGINEERING LEARN.PREDICT.INDUSTRIALISE Data Culture : Disrupting with data Gary Richardson, UK Head of Data Engineering KPMG
  56. 56. © 2015 KPMG LLP, a UK limited liability partnership, is a subsidiary of KPMG Europe LLP and a member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative ("KPMG International"), a Swiss entity. All rights reserved. Disruptor or disrupted?
  57. 57. © 2015 KPMG LLP, a UK limited liability partnership, is a subsidiary of KPMG Europe LLP and a member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative ("KPMG International"), a Swiss entity. All rights reserved. Key concepts that are driving data innovation Schema on read Open API’s Cloud ScaleModel Portability Automation
  58. 58. © 2015 KPMG LLP, a UK limited liability partnership, is a subsidiary of KPMG Europe LLP and a member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative ("KPMG International"), a Swiss entity. All rights reserved. Increasing the return from data value chain Data Processing Data Collection Data Science Predict Action Value Creation Value Protectio n Collect everything Process on demand Look for opportunities Making Predictions
  59. 59. © 2015 KPMG LLP, a UK limited liability partnership, is a subsidiary of KPMG Europe LLP and a member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative ("KPMG International"), a Swiss entity. All rights reserved. Discover patterns in data streaming automatically from remote sensors and machines Research logs to diagnose process failures and prevent security breaches Understand how your customers feel about your brand and products – right now Analyze location-based data to manage operations where they occur Understand patterns in files across millions of web pages, emails, and documents Geographic Unstructured Server Logs Sentiment Sensors New Data types Ever increasing volume, variety and velocity of data Leveraging new types of data Only by leveraging new types of data both internal and external can real value of analytics be unlocked
  60. 60. © 2015 KPMG LLP, a UK limited liability partnership, is a subsidiary of KPMG Europe LLP and a member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative ("KPMG International"), a Swiss entity. All rights reserved. Traditional Organisations = Legacy, change is needed Schema on read Open API’s CloudModel Portability AutomationStreaming Data Getting the data in Applying the machine
  61. 61. © 2015 KPMG LLP, a UK limited liability partnership, is a subsidiary of KPMG Europe LLP and a member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative ("KPMG International"), a Swiss entity. All rights reserved. High level data science workflow feature selection and scoring Product Search Observable Event Product Recommendation Feature Selection Process Recommendation Take Action Machine Learning Platform Score Features using Algorithms for the Event
  62. 62. © 2015 KPMG LLP, a UK limited liability partnership, is a subsidiary of KPMG Europe LLP and a member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative ("KPMG International"), a Swiss entity. All rights reserved. Use in Production Score in real-time the decision for which the model was trained Primary data manipulation and management Model build pipeline process Observable set of data that needed to be passed down the pipeline Select Feature Feature Transformation Train the model Train, validate, adjust, relearn, set curriculum of the model Publish API Publish the API to enable model to be utilised Monitor and Evaluate Continuous monitoring of model performance Re-trainmodel
  63. 63. © 2015 KPMG LLP, a UK limited liability partnership, is a subsidiary of KPMG Europe LLP and a member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative ("KPMG International"), a Swiss entity. All rights reserved. GLM K-Means Neural Networks Algorithms SVM Naïve Bayes Recommenders Cox Prop HazardsRandom Forests PCA Common algorithms Training Data
  64. 64. © 2015 KPMG LLP, a UK limited liability partnership, is a subsidiary of KPMG Europe LLP and a member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative ("KPMG International"), a Swiss entity. All rights reserved. Where are the opportunities for you? Data Science Insight Backed Products Data Marketplaces Big Compute Platforms
  65. 65. © 2015 KPMG LLP, a UK limited liability partnership, is a subsidiary of KPMG Europe LLP and a member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative ("KPMG International"), a Swiss entity. All rights reserved. Being creative with data even with the humble help desk call Contagion Risk 9.1 million service calls processed from start to finish in less than 4 hours 130 billion connected events identifying likely to cause of Contagion Graph Analysis Unstructured Data Processing
  66. 66. © 2015 KPMG LLP, a UK limited liability partnership, is a subsidiary of KPMG Europe LLP and a member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative ("KPMG International"), a Swiss entity. All rights reserved. Increasing Data Culture = Increases the Data Dividend
  67. 67. © 2015 KPMG LLP, a UK limited liability partnership, is a subsidiary of KPMG Europe LLP and a member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative ("KPMG International"), a Swiss entity. All rights reserved. The information contained herein is of a general nature and is not intended to address the circumstances of any particular individual or entity. Although we endeavour to provide accurate and timely information, there can be no guarantee that such information is accurate as of the date it is received or that it will continue to be accurate in the future. No one should act on such information without appropriate professional advice after a thorough examination of the particular situation. Gary Richardson Director, UK Head of Data engineering KPMG in the UK T: +44 20 7311 4019 E: gary.richardson@kpmg.co.uk Twitter: @garydata
  68. 68. #DataCulture Microsoft Data Culture - UK
  69. 69. Decision MakingOrganisation Data
  70. 70. Decision MakingOrganisation Data
  71. 71. Decision MakingOrganisation Data
  72. 72. Decision MakingOrganisation Data
  73. 73. Decision MakingOrganisation Data
  74. 74. Decision MakingOrganisation Data
  75. 75. Leadership Decision Making Data
  76. 76. Leadership Decision Making Data
  77. 77. Leadership Decision Making Data
  78. 78. Leadership Decision Making Data
  79. 79. Leadership Decision Making Data
  80. 80. Leadership Organisation Data
  81. 81. Leadership Organisation Data
  82. 82. Leadership Organisation Data
  83. 83. Leadership Organisation Data
  84. 84. Leadership Organisation Data
  85. 85. Leadership Decision MakingOrganisation
  86. 86. Leadership Decision MakingOrganisation
  87. 87. Leadership Decision MakingOrganisation
  88. 88. Leadership Decision MakingOrganisation
  89. 89. Leadership Decision MakingOrganisation
  90. 90. 129 Where to Look to get started EXAMPLE SOLUTIONS
  91. 91. 130 Example GiveGraph www.justgiving.com 81 Million nodes 361 Million Relationships
  92. 92. #DataCulture Microsoft Data Culture - UK
  93. 93. DATA SCIENCE&ENGINEERING LEARN.PREDICT.INDUSTRIALISE Building the DS&E team to maximise the data dividend
  94. 94. 133© 2015 KPMG LLP, a UK limited liability partnership and a member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative (“KPMG International”), a Swiss entity. All rights reserved. Structuring the team for success Data Science Data Engineering DevOps • Machine Learning • Deep Learning • Brittle Models • Industrialization • Software Development • Data Pipelines • Cluster Management • Cloud Orchestration • Automation
  95. 95. 134© 2015 KPMG LLP, a UK limited liability partnership and a member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative (“KPMG International”), a Swiss entity. All rights reserved. Head of Data Science Data Scientists Lead Data Scientist Data Engineers Senior Data Engineer DevOps Lead DevOps Data Science Data Engineering DevOps Product Management & Project Management Graduates Organization Structure
  96. 96. 135© 2015 KPMG LLP, a UK limited liability partnership and a member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative (“KPMG International”), a Swiss entity. All rights reserved. Ways of Working Confluence Jira Stash Bamboo Describe the outcome Delegate the work Control the code Automate the deployment
  97. 97. DATA SCIENCE&ENGINEERING LEARN.PREDICT.INDUSTRIALISE
  98. 98. #DataCulture Microsoft Data Culture - UK
  99. 99. Leverage the Edge Tune your business to embrace Machine Intelligence 138 What Should we do Today Build a Data Culture Plan Move beyond Big Data

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