I have been watching for Revolution Analytics product almost since the inception of the company. It has managed to sail over storms, naysayers and critics with simple and effective strategy of launching good software, making good partnerships and keeping up media visibility with white papers, joint webinars, blogs, conferences and events.
However this is a listing of all technical contributions made by Revolution Analytics products to the #rstats project.
1) Useful Packages mostly in parallel processing or more efficient computing like
- foreach (http://cran.r-project.org/web/packages/foreach/index.html) ,
- nws (http://cran.r-project.org/web/packages/nws/).
- iterators (http://cran.r-project.org/web/packages/iterators/index.html),
- doSMP (http://cran.r-project.org/web/packages/doSMP/index.html).
- doSNOW (http://cran.r-project.org/web/packages/doSNOW/index.html),
- doMC (http://cran.r-project.org/web/packages/doMC/index.html),
- revoIPC (http://cran.r-project.org/web/packages/revoIPC/)
2) RevoScaler package to beat R’s memory problem (this is probably the best in my opinion as it is yet to be replicated by the open source version and is a clear cut reason for going in for the paid version)
- Efficient XDF File Format designed to efficiently handle huge data sets.
- Data Step Functionality to quickly clean, transform, explore, and visualize huge data sets.
- Data selection functionality to store huge data sets out of memory, and select subsets of rows and columns for in-memory operation with all R functions.
- Visualize Large Data sets with line plots and histograms.
- Built-in Statistical Algorithms for direct analysis of huge data sets:
- Summary Statistics
- Linear Regression
- Logistic Regression
- On-the-fly data transformations to include derived variables in models without writing new data files.
- Extend Existing Analyses by writing user- defined R functions to “chunk” through huge data sets.
- Direct import of fixed-format text data files and SAS data sets into .xdf format
3) RevoDeploy R for API based R solution – I somehow think this feature will get more important as time goes on but it seems a lower visibility offering right now.
- Collection of Web services implemented as a RESTful API.
- .NET Client library — includes a COM interoperability to call R from VBA
- Management Console for securely administrating servers, scripts and users through HTTP and HTTPS.
- XML and JSON format for data exchange.
- Built-in security model for authenticated or anonymous invocation of R Scripts.
- Repository for storing R objects and R Script execution artifacts.
4) Revolutions IDE (or Productivity Environment) for a faster coding environment than command line. The GUI by Revolution Analytics is in the works. – Having used this- only the Code Snippets function is a clear differentiator from newer IDE and GUI. The code snippets is awesome though and even someone who doesnt know much R can get analysis set up quite fast and accurately.
- Full-featured Visual Debugger for debugging R scripts, with call stack window and step-in, step-over, and step-out capability.
- Enhanced Script Editor with hover-over help, word completion, find-across-files capability, automatic syntax checking, bookmarks, and navigation buttons.
- Run Selection, Run to Line and Run to Cursor evaluation
- R Code Snippets to automatically generate fill-in-the-blank sections of R code with tooltip help.
- Object Browser showing available data and function objects (including those in packages), with context menus for plotting and editing data.
- Solution Explorer for organizing, viewing, adding, removing, rearranging, and sourcing R scripts.
- Customizable Workspace with dockable, floating, and tabbed tool windows.
- Version Control Plug-in available for the open source Subversion version control software.
Marketing contributions from Revolution Analytics-
1) Sponsoring R sessions and user meets
2) Evangelizing R at conferences and partnering with corporate partners including JasperSoft, Microsoft , IBM and others at http://www.revolutionanalytics.com/partners/
3) Helping with online initiatives like http://www.inside-r.org/ (which is curiously dormant and now largely superseded by R-Bloggers.com) and the syntax highlighting tool at http://www.inside-r.org/pretty-r. In addition Revolution has been proactive in reaching out to the community
4) Helping pioneer blogging about R and Twitter Hash tag discussions , and contributing to Stack Overflow discussions. Within a short while, #rstats online community has overtaken a lot more established names- partly due to decentralized nature of its working.
Did I miss something out? yes , they share their code by GPL.
Let me know by feedback