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There is one consistent message we hear from customers across industries and around the world: "We would like to reduce our reliance on SAS." In this webinar, we review the top reasons customers cite …

There is one consistent message we hear from customers across industries and around the world: "We would like to reduce our reliance on SAS." In this webinar, we review the top reasons customers cite for moving fromSAS to R; the benefits of open source analytics; the challenges of switching; and the tools you will need to build your own roadmap. We review the key differences between SAS and R from the user's perspective, and provide you with the tools to move forward.

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- 1. Moving from SAS to R Thomas W. Dinsmore Seth Mottaghinejad August 7
- 2. Poll #1 What analytics platforms are you currently using? (please check all that apply) • R/RRE • SAS • SPSS • Tibco/Spotfire • Other 2
- 3. Revolution Confidential Moving from SAS to R Introduction Why choose R over SAS? Concerns about R How we can help How to Migrate from SAS to R Customer Success Questions
- 4. Revolution Confidential R: Explosive Growth Source: Rexer Data Miner Survey, 2007-2013 Use R R is Primary Tool 70%
- 5. Revolution Confidential Who uses R for analytics today? 5
- 6. Revolution Confidential 6 R Penetrates Enterprise Analytics 0 200 400 600 800 1,000 1,200 1,400 1,600 2014 2015 2016 2017 2018 Top 10 Global Bank – Planned Analytic Seats SAS R
- 7. Revolution Confidential 7 Why choose R over SAS?
- 8. Revolution Confidential 8 Your new analysts already know R.
- 9. Revolution Confidential 9 R is a comprehensive analytics platform.
- 10. Revolution Confidential 10 R is flexible and customizable.
- 11. Revolution Confidential 11 R is free; SAS is expensive.
- 12. Revolution Confidential 12 Concerns about R
- 13. Revolution Confidential 13 “We don’t know what’s in the code.”
- 14. Revolution Confidential 14 “We’ll be on our own.”
- 15. Revolution Confidential 15 “R doesn’t scale.”
- 16. Revolution Confidential 16 “We have a lot of SAS programs.”
- 17. Revolution Confidential 17 How we can help: “We don’t know what’s in the code.” “We’ll be on our own.” “R doesn’t scale.” “We have a lot of SAS programs.” Build Assurance Technical Support Distributed Platform Migration Services
- 18. Are you currently exploring alternative analytics platforms? • Yes • No Poll #2
- 19. Migrating from SAS to R: What you need to know 19
- 20. Revolution Confidential About me 20 Stats background Over 5 years R and SAS experience Worked on migrating SAS projects to R Teach a class on R for SAS users Passionate advocate bringing R to industry
- 21. Revolution Confidential 21 You may be… • New to R? • Using SAS and • think it is too expensive • think it does not integrate well with other apps • have a hard time attracting younger talent • curious about R • thinking of migrating to R • in the process of migrating to R • want to scale up to a Hadoop cluster or a traditional grid • Migration from SAS to R is doable.
- 22. Revolution Confidential 22 SAS vs R and RRE • Conceptually, SAS and R are very different languages, yet you can leverage a lot of what you know. Revolution Analytics has training and services to help you learn to work in R. • Often when switching from SAS to R we give up a pre-packaged solution in return for a flexible, robust solution that you can easily augment. • Writing code that works in R is easy, but writing production-level code in R is more difficult. • Through its ScaleR package, RRE brings to the table many of the features that make R an enterprise solution.
- 23. Revolution Confidential 23 SAS vs R and RRE • The explicit logic is the logic for implementing the project independent of any specific code. The implicit logic is the logic for implementing the project based on reading and understanding the code. • Can you diagram your project’s workflow (explicit logic)? • How much do you value adherence to the implicit logic (SAS code)? • If you had to rewrite the project, would you write the code in the same way or is there room for simplifying? • Was the project the work of a single person or did multiple people work on it?
- 24. Revolution Confidential 24 Migrating from SAS: DATA Step • Working with data (create, transform, and reshape) is straightforward in R. • If you use PROC SQL for many of your data operations, you may be able to bring most of it into R without having to rewrite it in R code, although this may not be the most efficient way. • You must act with caution in some cases, such as missing data or formatting issues. • How much data-processing do you perform? • What sorts of data sets do you import/read from?
- 25. Revolution Confidential 25 Migrating from SAS: PROCs • Except for a few notable cases (such as PROC IMPORT/EXPORT, TRANSPOSE) most PROCs in SAS are used to summarize data or to analyze data (modeling and data-mining). • Some statistical procedures may be implemented in a slightly different way in SAS vs R, resulting in tiny differences in computations. If such differences matter, we can always build on an existing solution or write our own. Creating a custom-made solution is far more easier in R than in SAS. • What statistical procedures do you use? • Do you want to exactly replicate your SAS code?
- 26. Revolution Confidential 26 Migrating from SAS: Macros • Macros in SAS are a “separate” language, built on top of the SAS language. You write SAS code to manipulate and analyze data, and you write macros to manipulate the SAS code itself, with the intention of automating the code. • There is no “R macro language”: R is flexible enough to also be its own macro language. However, in the case of more advanced macros, this often means that the converted R code will look very different from its SAS counterpart. • Do you use macros? If so, can you provide examples?
- 27. Revolution Confidential 27 Migrating from SAS: ODS • ODS is SAS’s way of exporting results to other formats. It can be used as part of a pipeline or for reporting. • The fact that R is open-source makes it even easier to create hookups to external formats (Excel, PDFs, HTML, etc.), which results in even more flexibility. • Can you describe your pipeline/workflow? • What formats do you export to? Who is the target audience (e.g. internal vs external)?
- 28. Revolution Confidential 28 Migrating from SAS: What else? • SAS has more components than covered so far, e.g. SAS Enterprise Miner, SAS EG, SAS IML, add-ons for design and analysis of experiments, and more. • R’s ease of integration with third party tools makes it very easy to extend its capability. • What are some specific SAS features that you want to migrate into R? • What are some concerns you might have about migrating? • How are you preparing for the migration?
- 29. Revolution Confidential 29 Handover of the R project • For a successful handover, we need to think of ways to test the R code to ensure that it can replicate the SAS code. • Documentation will be provided and some on-site knowledge transfer may be needed. • Training is also an option. • How much of your data will you share? • Is the data you will share representative of your “best data” or your “worst data”? • What are your success criteria? • Who will be in charge of testing the code? • How do you envisage the knowledge transfer?
- 30. In what scenario would you consider supplementing your production analytics platform? (all that apply) • New data environment (Hadoop) • Research / Data Exploration • Improve performance for production systems • Lower costs for production systems • New production application development Poll #3
- 31. Revolution Confidential 31 Customer Success
- 32. Revolution Confidential 32 Old Solution New Solution
- 33. Revolution Confidential 33 Old Solution New Solution
- 34. Revolution Confidential 34 Old Solution New Solution
- 35. Revolution Confidential Moving from SAS to R Introduction Why choose R over SAS? Concerns about R How we can help How to Migrate from SAS to R Customer Success Questions
- 36. Revolution Confidential 36
- 37. Join us in September Merkle will share their experience building a multi-channel customer analytics system with RRE, Cloudera and Tableau You can register on the Revolution Analytics website next week. 23SEP14 at 10:00 AM, Pacific 37

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