Introduction to Microsoft R Open
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Presented by David Smith, R Community Lead, Jan 28 2015 Data Science is a strategic initiative for most companies today, who seek to understand the wealth of data now available to them to understand patterns, make forcecasts, and build data-driven products and process. The open-source R language is the lingua franca of data science, and ranked #6 in popularity amongst all languages by the IEEE. If you haven’t yet learned what R is all about, this webinar will bring you up to speed on the history of the R language, how it’s used, and why it’s so popular for developing advanced analytics applications. In this 50-minute webinar, David Smith, R Community Lead at Microsoft, will introduce the R language and community, and give examples of R in action. In the webinar, David will demonstrate Microsoft R Open, Microsoft’s enhanced distribution of open-source R. He will also cover the enhancements included in Microsoft R Open, including enhanced performance, features for reproducible programming in R, and the new CRAN Time Machine for reproducible data analysis with R packages.
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Introduction to Microsoft R Open
- 2. January 28, 2015 — Welcome! What is R? Applications of R Microsoft R Open Demo Q&A David Smith R Community Lead Microsoft @revodavid Editor, Revolutions blog blog.revolutionanalytics.com Co-author (with Bill Venables and R Core Team), An Introduction to R cran.r-project.org/manuals.html
- 3. Which statement best matches your relationship to R? - I’m completely new to R, but want to learn - I’m learning R - I’m an experienced R user - I won’t be using R (but I’m interested in what it can do)
- 5. CRAN Task View by Barry Rowlingson: http://www.maths.lancs.ac.uk/~rowlings/R/TaskViews/
- 6. Photo credit: Robert Gentleman
- 7. R Usage Growth Rexer Data Miner Survey, 2007-2015 Language Popularity IEEE Spectrum Top Programming Languages, 2015 76% of analytic professionals report using R 36% select R as their primary tool
- 10. New York Times, June 25 2009 (3 hours after Michael Jackson’s death)
- 11. • Credit Risk Analysis • Financial Networks
- 12. Facebook • Exploratory Data Analysis • Experimental Analysis “Generally, we use R to move fast when we get a new data set. With R, we don’t need to develop custom tools or write a bunch of code. Instead, we can just go about cleaning and exploring the data.” — Solomon Messing, data scientist at Facebook
- 13. Housing • Crime mapping “The core innovation that Zillow offers are its advanced statistical predictive products, including the Zestimate®, the Rent Zestimate and the ZHVI® family of real estate indexes. By using R in production as well as research, Zillow maximizes flexibility and minimizes the latency in rolling out updates and new products.” • Statistical forecasting
- 14. The Azure Cloud Operational Announced Central US Iowa West US California North Europe Ireland East US Virginia East US 2 Virginia US Gov Virginia North Central US Illinois US Gov Iowa South Central US Texas Brazil South Sao Paulo West Europe Netherlands China North * Beijing China South * Shanghai Japan East Saitama Japan West OsakaIndia West TBD India East TBD East Asia Hong Kong SE Asia Singapore Australia West Melbourne Australia East Sydney * Operated by 21Vianet
- 18. Benchmarks details at MRAN
- 20. Adapted from http://xkcd.com/234/ CC BY-NC 2.5
- 21. Any updated package = potential reproducibility error! http://blog.revolutionanalytics.com/2014/10/explore-r-package-connections-at-mran.html
- 23. (Any date after Sep 17, 2015)
- 24. If you’re an R user, have you tried Microsoft R Open (or Revolution R Open)? - I’ve never tried Microsoft R Open - I’ve tried Microsoft R Open - I primarily use Microsoft R Open - I don’t use R
- 26. Microsoft R Server Big-data analytics and distributed computing on Linux, Hadoop and Teradata SQL Server 2016 Big-data analytics integrated with SQL Server database (coming soon) PowerBI Computations and charts from R scripts in dashboards Azure ML Studio R Scripts in cloud-based Experiment workflows Visual Studio R Tools for Visual Studio: integrated development environment for R (coming soon) HDInsights R integrated with cloud-based Hadoop clusters Cortana Analytics Cloud-based R APIs and Virtual Machines
- 27. Thursday, February 4 Using Microsoft R Server to Address Scalability Issues in R Thursday, February 11 Data Mining with Microsoft R Server Thursday, February 18 Best Practices for using Microsoft R Server with Hadoop Thursday, February 25 Using Microsoft R Server to Operationalize your Analytics info.microsoft.com/Microsoft-R-Webinars.html
- 31. Trends
Notas del editor
- Credit Suisse: http://blog.revolutionanalytics.com/2013/05/sheftel-on-r-on-the-trading-desk.html ANZ: http://blog.revolutionanalytics.com/2011/08/how-anz-uses-r-for-credit-risk-analysis.html American Century: http://blog.revolutionanalytics.com/2013/06/american-century-investments.html
- http://strataconf.com/stratany2012/public/schedule/detail/26345 Zillow Trulia http://blog.revolutionanalytics.com/2011/06/the-residuals-of-crime.html
- Over the last few years we’ve truly delivered a huge infrastructure to enable us to grow our services at scale around the globe. Whether it’s our flagship facilities in Quincy, Washington or Boydton, Virginia, or some of the newly announced facilities in Shanghai, Australia and Brazil, it really is key for us to make smart investments around the world to deliver services in a resilient and reliable fashion. A lot of people ask, what goes into site selection at Microsoft and how do we decide where to place our datacenter investments? There are over thirty-five factors in our site selection criteria. But really, the top elements are around proximity to customers and energy and fiber infrastructure, insuring that we have the capacity and the growth platforms to be able to grow our services. Another key element is about skilled workforce. We need to insure that we have the right people to run and operate our datacenters on a day to day basis.
- Infinite scale inexpensively Tons of data from which you actually have to get value Customers that have a very high expectation of service and connection – Pier 1 great example Influx of new talent to fill a very big gap McKinsey says is 300 thousand in US alone But the market this new talent is entering is still filled with barriers