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Analytics with R in SQL Server 2016
- Analytics with R in SQL Server 2016 discusses how SQL Server 2016 integrates the popular R programming language for analytics. - It introduces R and highlights challenges like data movement and scale/performance that SQL Server with R addresses. - SQL Server with R features like in-database analytics, T-SQL stored procedures, and RevoScaleR support help overcome challenges by reducing data movement, enabling operationalization, and leveraging in-memory processing and parallelism to improve scale and performance of R scripts. - The presentation demonstrates R tools in SQL Server and an end-to-end scenario of data exploration, predictive modeling, and operationalizing R code with different roles.
Analytics with R in SQL Server 2016
- 1. Analytics with Rin SQL Server 2016 Chennai SQL Server User Group
- 2. Hariharan Lead Consultant, YourSQL Man (I) Pvt Ltd Microsoft Certified Trainer Microsoft Certified Solution Expert Business Intelligence & Data Management and Analytics SAP HANA & Business Objects Active Speaker in DAGEOP DATA DAY Blog http://dataap.org/author/hariharanr/ Twitter @imhariharanr Linked In hariharan-r-12635640
- 3. Topics • Analytics • Introductionto R • Challenges • R in SQL Server 2016 • Advanced Analytics in R • Visualization with R 3
- 4. Analytics What Happened? Why Happened? What Will happen? Whatshould I do? Descriptive Diagnostic Predictive Prescriptive
- 5. Introduction to R •It is a Open Source • A statistics programming language • A data visualization tool • It has a very big community with 2.5+ M users • Scalable to big data • Rich application & platform integration
- 6. Introduction to R 0 500 1000 1500 2000 2500 3000 3500 4000 20112012 2013 2014 2015 2016 R Packages in CRAN
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- 8. Challenges in R •Data Movement • Moving data from database to R • Operationalization • How do I call R script from my application • Scale and Performance • R runs in single threaded and only accommodates datasets that fit into available memory
- 9. SQL Server withR • Data Movement • Reduce or eliminate data movement with In-Database analytics • Operationalization • T-SQL Stored Procedure • Scale and Performance • In-memory, columnstore indexes. Leverage RevoScaleR support large datasets and parallel algorithms
- 10. SQL Server withR • It a new feature in SQL Server 2016 • New Workload • Integrated highly popular R language for enterprise customers • Intelligent & Predictive Applications
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- 12. R Components DeployR • RESTfulAPIs for easy integration from java, • JavaScript, .NET • Enterprise authentication & security • Horizontal Scaling ConnectR • High-speed & direct connectors Available for: • High performance XDF • SAS, SPSS, delimited & fixed format text data files • Hadoop HDFS (text & XDF) • Teradata Database & Aster • EDWs and ADWs • ODBC DevelopR • Develop R using familiar tools • RTVS • R Studio • R Client SclaeR • Ready-to-use high performance big data analytics • Fully-parallelized analytics • Data prep & data distillation • Descriptive statistics & statistical tests • Range of predictive functions • Wide data sets supported – thousands of variables DistributedR • Distributed computing framework • Delivers cross-platform portability CRAN • Open source R interpreter • Freely available huge range of R algorithms (packages) • Huge community of users Microsoft R Open • Based on open source R • High performance math library to speed up linear algebra functions • Checkpoint package to easily share R code and replicate results using specific R package versions
- 13. Tools • Microsoft RClient • Microsoft R Open • Visual Studio R Tools • R Studio • R GUI
- 14. End to EndScenario Developer DBA Data Engineer Data Scientist Data Exploration and Predicative Modeling Operationalizing the R Code Managing my server Authoring workflows
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- 19. Advanced Analytics -R & Data Optimization SQL Server R Client • ScaleR Library • Compute Context • Parallel Processing • Algorithm Parameters
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