Data Culture Series - Keynote & Panel - 19h May - London
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The document outlines the Data Culture Series event held on May 19, 2015, in London, focusing on how businesses utilize data and predictive analytics to drive transformation. It highlights the shift towards cloud deployment and the importance of data-driven insights for organizational success. Key presentations include discussions on the Microsoft data platform, advancements in analytics, and workshops related to big data and machine learning.
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Data Culture Series - Keynote & Panel - 19h May - London
- 1. DATA CULTURESERIES – 19th May 2015 London
- 2. ?Who is using Data to drive the future of their business?
- 3. ?Who is using Predictive Analytics / Machine Learning yet to change their business model?
- 4. UK Business Lead for BI & Advanced Analytics 4 Jon Woodward : Connect & Follow 4 @JLWoodward www.linkedin.com/in/jonathanwoodward #DataCulture SQL Server PowerBI AzureML Hadoop DataFactory DocumentDB Search EventHub Stream Analytics Revolution R Azure DW Azure Data Lake
- 5. Industry transformation driving opportunities
- 6. 2015…We have reached a Tipping Point Of organizations will consider cloud deployment 50% Of new licence spend will be for Data Discovery & Analytics 50% Of BI & Analytics spend will be driven by the Business 50% Of Users will be touched by BI and Analytics 50%
- 7. Core to Vision Start Justin Digital Work & Life Experiences
- 9. UK Economy - data dividend
- 10. The Microsoft data platform MobileReports Natural language queryDashboardsApplications StreamingRelational Internal & externalNon-relational NoSQL Orchestration Machine learningModeling Information management Complex event processing
- 13. Data Culture Series Data Culture Exec Session Data Culture Summit 4 events – final event 14th May, London CXO Level – Invite only 10 events; 1000 customers Power User, Analyst, Architect, Developer, DBA, Data Scientist Final event this fiscal ( London)
- 16. Date Location 19 May LONDON Data Culture series Summer Break Date Location September 16 th /17 th London 2 Day Data Culture Event - http://bit.ly/MSFTDataCulture Nov 10-11 th London Future Decoded - https://futuredecoded.microsoft.com/ Jan TBC 2 Day Data Culture Event
- 17. Value of Data IoT Business Apps CMO, CFO, Sales Business Case For Data CDO, CIO, CTO Architect Level Data Platform Workshop Modernising your Data Platform Data Developer Multi-track - Hands-on BI, Advanced Analytics , IoT, Data Services, Big Data Dashboard in a Day Analyst Hands on BI
- 18. #DataCulture Microsoft Data Culture - UK
- 19. Time 10.00 – 10.30 Intro – Jon Woodward 10:30 – 11:30 Keynote Phillip Watson – Business Applications and Data Neil Miller – Revolution Analytics Overview 11:30 – 12:30 Immersion Tracks - Overview 12:30 – 13:15 Lunch & Expo 13:15 – 15:00 Immersion Hands on 15:00 - 15:15 Break & Expo 15:15 - 16:30 Immersion Hands on 16:30 – 17:00 Panel and l Close Microsoft, HortonWorks, KPMG, Revolution
- 20. PHILLIP WATSONBusiness Applications and Data
- 22. R&D, Plan Source, Supply BOM
- 24. 24 An Example in Practise
- 26. 26
- 28. “Understand,UnlockandEmpoweryourorganisationtogainacompetitiveedgethroughdatadriveninsight”. Date: Thursday, June 25, 2015 Time: 01:00 PM British Summer Time Duration: 1 hour Understandhowinformationcanunderpinthedeliveryofexceptionalcustomercareatthewebinar “CareEverywhere–Howtoamaze,delightandexceedyourcustomers’highexpectations” Date: Thursday, June 25, 2015 Time: 01:00 PM British Summer Time Duration: 1 hour
- 29. Take a look at the Business Intelligence capabilities that Microsoft Dynamics AX can surface here & Microsoft Dynamics CRM here • If you want to discuss how business applications can link with your decision making processes contact Martin Lloyd on [email protected]
- 30. NEIL MILLER Revolution Analytics Overview Bigger Data with R
- 32. BIGGER Data? R Revolution R Enterprise Revolution Analytics Proprietary
- 33. (A Zettabyte has 21 zeros) (40,000,000,000,000,000,000,000) (= 3 million books per person) Volume Variety Velocity Revolution Analytics Proprietary
- 34. But… • Wider data sets (many more variables / features) • Real time scoring (steaming data in fast…) Revolution Analytics Proprietary
- 36. THE PERFECT STORM + Computing Power + Bigger Data / More Data + Pace of Business + Customer Expectations + Data Science + Computer Science + Management Science Better Business Decisions Better Business Outcomes Revolution Analytics Proprietary
- 37. - Robert Gentleman & Ross Ihaka, 1993 - Version 1.0 in 2000 - 3.0+ Million Global Users - 6200+ “Packages” - R in Universities = New Talent - Open Source = Access To Innovation - Programming Agility - Huge range of predictive analytics We love R! Revolution Analytics Proprietary
- 39. Revolution R Enterprise solves these problems! ? Revolution Analytics Proprietary
- 40. OUR COMPANY The leading provider of advanced analytics software and services based on open source R, since 2007 OUR PRODUCTS REVOLUTION R: The enterprise-grade predictive analytics application platform based on the R language Revolution Analytics Proprietary
- 41. Language Interpreter and Standard R Algorithm Suites Development & Deployment Tooling Big Data Distributed Execution Platform R+CRAN RevoR DistributedR ConnectR ScaleR DevelopR DeployR Revolution R Enterprise Big Data Big Analytics Ready – Enterprise readiness – High performance analytics – Multi-platform architecture – Data source integration – Development tools and Integration tools Enterprise Technical Support Revolution Analytics Proprietary
- 43. File Name Compressed File Size (MB) No. Rows Open Source R (secs) Revolution R (secs) Tiny 0.3 1,235 0.001 0.05 V. Small 0.4 12,353 0.21 0.05 Small 1.3 123,534 0.03 0.03 Medium 10.7 1,235,349 1.94 0.08 Large 104.5 12,353,496 60.69 0.42 Big (full) 12,960.0 123,534,969 Memory! 4.89 V.Big 25,919.7 247,069,938 Memory! 9.49 Huge 51,840.2 494,139,876 Memory! 18.92 22 years of US flight data 124m rows, 29 variables Linear Regression model - arrival delay as function of day-of-week Tests run on 4 core machine, 16GB RAM and 500GB SSD Revolution Analytics Proprietary
- 44. DistributedR ScaleR ConnectR DeployR In the Cloud Cloud Workstations & Servers Desktops Server Clustered Systems Microsoft HPC Linux EDW Teradata Hadoop Hortonworks Cloudera MapR + HD Insights + SQL Server vNext + Azure ML + Power BI Revolution Analytics Proprietary
- 45. In-database analytics at massive scale Data Scientist Interact directly with data SQL Server Data Developer/DBA Manage data and analytics together ExtensibilityExample Solutions • Fraud detection • Salesforecasting • Warehouse efficiency • Predictive maintenance 010010 100100 010101 Relational Data Analytic Library Native functions T-SQL Interface Benefits Faster deployment of ML models Faster performance (Move compute to the data) Improved scalability In-DB Analytic Scenarios Real-time fraud detection Customer churn analysis Product recommendations R RIntegration coming! Microsoft Confidential. Preliminary Information. Dates and capabilities subject to change. Microsoft makes no warranties, express or implied. Revolution Analytics Proprietary
- 46. Assemble and standardize all of a marketer’s data into a Hadoop cluster Apply the rigor of a medical researcher with patented methodology Know whom to reach Identify and attribute the revenue drivers Revolution Analytics Proprietary More info at: http://www.revolutionanalytics.com/content/datasong%E 2%80%99s-big-data-analytics-platform-marketing- optimization-helps-clients-understand
- 47. Features Ensemble of models used: SVM, Random Forests, and Neural Networks. Then Logistic Regression used to assess pass / fail Pass Or Fail Pre-processing crop and align to fixed size. More info at : http://info.revolutionanalytics.com /30apr15-iot-and-the- manufacturing-floor.html Revolution Analytics Proprietary HOG (Histogram Orientated Gradients) Feature Selection Each value is a composite (histogram) of multiple pixels
- 48. Hadoop Edge & Data Node2 x Data Node • Use new 3rd party data-sources of categorical data to automatically create new variables (features). e.g consumer spend across various categories, locations etc. • Split and analyze features in parallel to measure predictive quality for credit-risk and default • Champion / Challenger: Select top ‘n’ new features and compare against existing features in credit risk models. • Introduce new “Golden” features once proven to enhance model • Legacy solution took several months to code with 6 week run process (with manual intervention). Unsuitable for production runs! • Revolution code implemented in Hadoop using massive parallel processing machine-learning to automate feature selection. • 6 weeks processing reduced to a < 24 hour automated execution process External 3rd Party Data Sources Customer Credit Process Revolution Analytics Proprietary
- 49. What next? • If you are using R (or SAS, SPSS, Matlab…) today and need scale, speed, support and get on the road to Microsoft Advanced Analytics come and talk to us! • [email protected] • [email protected] • More info? www.revolutionanalytics.com Revolution Analytics Proprietary
- 50. Tracks Rooms
- 51. DATA CULTURESERIES – 19th May 2015 London - Panel
- 52. Ric Howe - [email protected] Microsoft Tim Marston - [email protected] HortonWorks Andrew Morgan - [email protected] KPMG Neil Miller - [email protected] Revolution Analytics
- 53. #DataCulture Ric (Microsoft) Q : With all the recent announcements at //Build and Ignite, what aspects should we be most excited about
- 54. #DataCulture Andrew M (KPMG) Q : Does Data Science really require Data Scientists
- 55. #DataCulture Tim M (Hortonworks) Q : if Hadoop is the answer to Big Data, where is it heading…what is the future vision
- 56. #DataCulture Neil M(Revolution) Q : Analytics and R is such as hot topic – how should be start?
- 57. Trial : Revolution R Open Trial : Hadoop (HDInsight, HDP) 57 Get Hands on… Trial : SQL Server 2014 Trial : PowerBI Trial : Machine Learning (AzureML)
- 58. SQL Saturday – Manchester , July 25th SQL Relay , October 12-22nd – 8 Locations PASS BA*, London , November PASS Summit*- US, October 27-30th SQL Saturday – Edinburgh , June 13th 58 Community Events 58 * See Jen Stirrup for Discount
- 60. 60 SQL London Chapter (Tonight) 6:00 - 6:10 PASS Chapter Updates 6:10 - 7:10pm Allan Mitchell (MVP) - DocumentDB 7:10 - 7:40pm Break & Networking 7:40 - 8:40pm Tobiasz Koprowski (MVP) - WASD for Beginners Linked In: http://www.sqlpass.org/linkedin Facebook: http://www.sqlpass.org/facebook Twitter: @SQLPASS PASS: http://www.sqlpass.org
- 61. Learn More: Microsoft Azure • Microsoft Azure Consulting Sessions – Apply Now to 27th May • Contact our Azure advisory team at [email protected] • Tech Days Online – Azure Special: 2nd-4th June • Developer showcases, demos and deep technical learning with MS experts • http://aka.ms/tdoazure
- 62. Learn More: Internet of Things & Data • Developing for Internet of Things: http://aka.ms/iotworkshop • Download the Hands On Lab • June 11th Reading: 1-Day IoT & Data “Hackathon” hands on learning • Waitlist registrants receive 1st priority for next event • Machine Learning without a PhD • Watch the Webinar http://aka.ms/azuremlwebinar • Download the hands on lab http://aka.ms/machinelearninglab • Join the IoT Community Group: 9th June Focus Group • Connect with Microsoft and others in IoT. • Contact [email protected]
- 63. Get Ready for September.. Date Location 16 September READING 10 November LONDON 27 November READING 3 December LONDON 27 January LONDON 24 February LEEDS 24 March EDINBURGH 8 April BIRMINGHAM 12 May READING 19 May LONDON Have a great Summer….
- 64. UK Business Lead for BI & Advanced Analytics 64 Jon Woodward : Connect & Follow 64 @JLWoodward www.linkedin.com/in/jonathanwoodward #DataCulture
- 65. THANK YOU ?