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Here is a brief interview with Alvaro Tejada Galindo aka Blag who is a developer working with SAP Hana and R at SAP Labs, Montreal. SAP Hana is SAP’s latest offering in BI , it’s also a database and a computing environment , and using R and HANA together on the cloud can give major productivity gains in terms of both speed and analytical ability, as per preliminary use cases.
Ajay- What made the R language a fit for SAP HANA. Did you consider other languages? What is your view on Julia/Python/SPSS/SAS/Matlab languages
Blag- I think “R” is a must for SAP HANA. As the fastest database in the market, we needed a language that could help us shape the data in the best possible way. “R” filled that purpose very well. Right now, “R” is not the only language as “L” can be used as well (http://wiki.tcl.tk/17068) …not forgetting “SQLScript” which is our own version of SQL (http://goo.gl/x3bwh) . I have to admit that I tried Julia, but couldn’t manage to make it work. Regarding Python, it’s an interesting question as I’m going to blog about Python and SAP HANA soon. About Matlab, SPSS and SAS I haven’t used them, so I got nothing to say there.
Ajay- What is your view on some of the limitations of R that can be overcome with using it with SAP HANA.
Blag- I think mostly the ability of SAP HANA to work with big data. Again, SAP HANA and “R” can work very nicely together and achieve things that weren’t possible before.
Ajay- Have you considered other vendors of R including working with RStudio, Revolution Analytics, and even Oracle R Enterprise.
Blag- I’m not really part of the SAP HANA or the R groups inside SAP, so I can’t really comment on that. I can only say that I use RStudio every time I need to do something with R. Regarding Oracle…I don’t think so…but they can use any of our products whenever they want.
Ajay- Do you have a case study on an actual usage of R with SAP HANA that led to great results.
Blag- Right now the use of “R” and SAP HANA is very preliminary, I don’t think many people has start working on it…but as an example that it works, you can check this awesome blog entry from my friend Jitender Aswani “Big Data, R and HANA: Analyze 200 Million Data Points and Later Visualize Using Google Maps “ (http://allthingsr.blogspot.com/#!/2012/04/big-data-r-and-hana-analyze-200-million.html)
Ajay- Does your group in SAP plan to give to the R ecosystem by attending conferences like UseR 2012, sponsoring meets, or package development etc
Blag- My group is in charge of everything developers, so sure, we’re planning to get more in touch with R developers and their ecosystem. Not sure how we’re going to deal with it, but at least I’m going to get myself involved in the Montreal R Group.
|Name:||Alvaro Tejada Galindo|
|Company:||SAP Canada Labs-Montreal|
|Instant Messaging Type:|
|Instant Messaging ID:||Blag|
|Professional Blog URL:||http://www.sdn.sap.com/irj/scn/weblogs?blog=/pub/u/252210910|
|My Relation to SAP:||employee|
|Short Bio:||Development Expert for the Technology Innovation and Developer Experience team.Used to be an ABAP Consultant for the last 11 years. Addicted to programming since 1997.|
SAP HANA is SAP AG’s implementation of in-memory database technology. There are four components within the software group:
- SAP HANA DB (or HANA DB) refers to the database technology itself,
- SAP HANA Studio refers to the suite of tools provided by SAP for modeling,
- SAP HANA Appliance refers to HANA DB as delivered on partner certified hardware (see below) as anappliance. It also includes the modeling tools from HANA Studio as well replication and data transformation tools to move data into HANA DB,
- SAP HANA Application Cloud refers to the cloud based infrastructure for delivery of applications (typically existing SAP applications rewritten to run on HANA).
R is integrated in HANA DB via TCP/IP. HANA uses SQL-SHM, a shared memory-based data exchange to incorporate R’s vertical data structure. HANA also introduces R scripts equivalent to native database operations like join or aggregation. HANA developers can write R scripts in SQL and the types are automatically converted in HANA. R scripts can be invoked with HANA tables as both input and output in the SQLScript. R environments need to be deployed to use R within SQLScript
More blog posts on using SAP and R togetherDealing with R and HANA
HANA meets R
When SAP HANA met R – First kiss
Using RODBC with SAP HANA DB-
SAP HANA: My experiences on using SAP HANA with R
and of course the blog that started it all-
Jitender Aswani’s http://allthingsr.blogspot.in/
Here is an interview with Kelci Miclaus, a researcher working with the JMP division of the SAS Institute, in which she demonstrates examples of how the R programming language is a great hit with JMP customers who like to be flexible.
Ajay- How has JMP been using integration with R? What has been the feedback from customers so far? Is there a single case study you can point out where the combination of JMP and R was better than any one of them alone?
Kelci- Feedback from customers has been very positive. Some customers are using JMP to foster collaboration between SAS and R modelers within their organizations. Many are using JMP’s interactive visualization to complement their use of R. Many SAS and JMP users are using JMP’s integration with R to experiment with more bleeding-edge methods not yet available in commercial software. It can be used simply to smooth the transition with regard to sending data between the two tools, or used to build complete custom applications that take advantage of both JMP and R.
One customer has been using JMP and R together for Bayesian analysis. He uses R to create MCMC chains and has found that JMP is a great tool for preparing the data for analysis, as well as displaying the results of the MCMC simulation. For example, the Control Chart platform and the Bubble Plot platform in JMP can be used to quickly verify convergence of the algorithm. The use of both tools together can increase productivity since the results of an analysis can be achieved faster than through scripting and static graphics alone.
I, along with a few other JMP developers, have written applications that use JMP scripting to call out to R packages and perform analyses like multidimensional scaling, bootstrapping, support vector machines, and modern variable selection methods. These really show the benefit of interactive visual analysis of coupled with modern statistical algorithms. We’ve packaged these scripts as JMP add-ins and made them freely available on our JMP User Community file exchange. Customers can download them and now employ these methods as they would a regular JMP platform. We hope that our customers familiar with scripting will also begin to contribute their own add-ins so a wider audience can take advantage of these new tools.
Ajay- Are there plans to extend JMP integration with other languages like Python?
Kelci- We do have plans to integrate with other languages and are considering integrating with more based on customer requests. Python has certainly come up and we are looking into possibilities there.
Ajay- How is R a complimentary fit to JMP’s technical capabilities?
Kelci- R has an incredible breadth of capabilities. JMP has extensive interactive, dynamic visualization intrinsic to its largely visual analysis paradigm, in addition to a strong core of statistical platforms. Since our brains are designed to visually process pictures and animated graphs more efficiently than numbers and text, this environment is all about supporting faster discovery. Of course, JMP also has a scripting language (JSL) allowing you to incorporate SAS code, R code, build analytical applications for others to leverage SAS, R and other applications for users who don’t code or who don’t want to code.
JSL is a powerful scripting language on its own. It can be used for dialog creation, automation of JMP statistical platforms, and custom graphic scripting. In other ways, JSL is very similar to the R language. It can also be used for data and matrix manipulation and to create new analysis functions. With the scripting capabilities of JMP, you can create custom applications that provide both a user interface and an interactive visual back-end to R functionality. Alternatively, you could create a dashboard using statistical and/or graphical platforms in JMP to explore the data and with the click of a button, send a portion of the data to R for further analysis.
Another JMP feature that complements R is the add-in architecture, which is similar to how R packages work. If you’ve written a cool script or analysis workflow, you can package it into a JMP add-in file and send it to your colleagues so they can easily use it.
Ajay- What is the official view on R from your organization? Do you think it is a threat, or a complimentary product or another statistical platform that coexists with your offerings?
Kelci- Most definitely, we view R as complimentary. R contributors are providing a tremendous service to practitioners, allowing them to try a wide variety of methods in the pursuit of more insight and better results. The R community as a whole is providing a valued role to the greater analytical community by focusing attention on newer methods that hold the most promise in so many application areas. Data analysts should be encouraged to use the tools available to them in order to drive discovery and JMP can help with that by providing an analytic hub that supports both SAS and R integration.
Ajay- While you do use R, are there any plans to give back something to the R community in terms of your involvement and participation (say at useR events) or sponsoring contests.
Kelci- We are certainly open to participating in useR groups. At Predictive Analytics World in NY last October, they didn’t have a local useR group, but they did have a Predictive Analytics Meet-up group comprised of many R users. We were happy to sponsor this. Some of us within the JMP division have joined local R user groups, myself included. Given that some local R user groups have entertained topics like Excel and R, Python and R, databases and R, we would be happy to participate more fully here. I also hope to attend the useR! annual meeting later this year to gain more insight on how we can continue to provide tools to help both the JMP and R communities with their work.
We are also exploring options to sponsor contests and would invite participants to use their favorite tools, languages, etc. in pursuit of the best model. Statistics is about learning from data and this is how we make the world a better place.
About- Kelci Miclaus
Kelci is a research statistician developer for JMP Life Sciences at SAS Institute. She has a PhD in Statistics from North Carolina State University and has been using SAS products and R for several years. In addition to research interests in statistical genetics, clinical trials analysis, and multivariate analysis/visualization methods, Kelci works extensively with JMP, SAS, and R integration.
I just saw this awesome case study of using Rapid Miner for predicting Churn in financial services (Paypal). I had been looking for simple yet exhaustive manuals/case studies on churn modeling and this is one the better ones I have seen. http://rapid-i.com/downloads/press/PayPalCaseStudyChurnRiskDetectionv1.1-web.pdf
Before you rev up those keyboards, and shoot off a snarky comment- consider this statement- there are many ways to run (and ruin economies). But they still have not found a replacement for money. Yes Happiness is important. Search Engine is good.
So unless they start a new branch of economics with lots more motivational theory and psychology and lot less quant especially for open source projects, money ,revenue, sales is the only true measure of success in enterprise software. Particularly if you have competitors who are making more money selling the same class of software.
Popularity contests are for high school quarterbacks —so even if your open source software is popular in downloads, email discussions, stack overflow or (more…)