Microsoft data analysis made easy
We implemented Microsoft R along side Windows Subsystem for Linux with Airflow to do ETL data loading last year through until late this …
Microsoft R Open / Revolution R Enterprise
Microsoft R Open / Revolution R Enterprise
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What is Microsoft R Open / Revolution R Enterprise?
Microsoft R Open and Revolution R Enterprise are big data R distribution for servers, Hadoop clusters, and data warehouses. Microsoft acquired original developer Revolution Analytics in 2016. Microsoft R is available in two editions: Microsoft R Open (formerly Revolution R Open) and Revolution R…
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Product Details
What is Microsoft R Open / Revolution R Enterprise?
Microsoft R Open and Revolution R Enterprise are big data R distribution for servers, Hadoop clusters, and data warehouses. Microsoft acquired original developer Revolution Analytics in 2016.
Microsoft R is available in two editions: Microsoft R Open (formerly Revolution R Open) and Revolution R Enterprise.
Microsoft R Open / Revolution R Enterprise Technical Details
| Operating Systems | Unspecified |
|---|---|
| Mobile Application | No |
Frequently Asked Questions
Microsoft R Open and Revolution R Enterprise are big data R distribution for servers, Hadoop clusters, and data warehouses. Microsoft acquired original developer Revolution Analytics in 2016.
Microsoft R is available in two editions: Microsoft R Open (formerly Revolution R Open) and Revolution R Enterprise.
Reviewers rate Single platform for multiple model development highest, with a score of 8.
The most common users of Microsoft R Open / Revolution R Enterprise are from Enterprises (1,001+ employees) and the Computer Software industry.
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November 30, 2020
Microsoft data analysis made easy
We implemented Microsoft R along side Windows Subsystem for Linux with Airflow to do ETL data loading last year through until late this year. We had some success with both products but due to limitations to Airflow and R not being completely fully functioning versus open source R suites we have cancelled both tools not long ago. I can say during its time it was easy to set up, R was easier to use to send processing jobs through than other solutions before and after. It just did not meet our needs once we got ETL loading to a more robust point.
- Easy to set up on a windows system and integrate to network drives for data integration.
- Allows easy authenticated user access to the tool to send jobs (one less user/pw on a domain).
- Easy to integrate to other windows applications that are installed beside the software on the same system and on other windows remote systems.
- Relatively low issues in the configuration phase to enable data processing.
- It is not fully featured vs linux open source versions out there.
- It is not as easy to find (or as much) online documentation when having issues with the software.
- Use of this tool alongside WSL applications is still too early. Once WSL gets more general use then this will be a better tool.
December 23, 2019
Cracking product, but steep learning curve.
My organisation has 40+ services ranging from 00s to millions of users, therefore iterations, changes and forecasting must be done in a controlled, rigorous and statistically appropriate manor as well as using tools that are efficient and provide analytics the ability to interrogate data en masse. R provides this.
- Comprehensive and highly populated repositories allowing for a lot of statistical work to be done quickly.
- Forecasting tools are solid and have provided quick and accurate insight.
- Very steep learning curve... for such a quick and useful tool the learning curve is unacceptable.
- Very dangerous in the wrong hands. Because most add-ons are pre-written, you have to trust the community that malicious script is not used.
January 26, 2019
Microsoft R - great for parallel processing!
Microsoft R is used by specific users when parallel processing is desired. Otherwise, most are fine with Base R.
- Parallel processing
- Integration with R
- Open-source
- R itself is a programming language, so there is some learning curve
- Sometimes interferes with upgrading R packages
November 27, 2018
R is great if you're looking for free/open source stat software
Microsoft R is typically used for statistics and data analysis needs for marketing data and developing machine learning algorithms. It helps solve optimization and developing predictive models. R is currently being used by one person in the department considering the size of the company, but looking to add more users of R sooner or later.
- It's free
- It's open source
- Does the same statistical and data analysis as other programs
- Very high learning curve
November 26, 2014
Revolution R Enterprise - Truly revolutionary product!!
I have used Revolution Analytics Rev-R enterprise 7.0 for data analytics project. I was also engaged in beta-testing release D as well. Rev-R actually solves a Big Data gap by allowing data scientists to load big data in Hadoop HDFS and run complex algorithms such as Random Forest or decision trees by running the algorithms in a distributed way on the cluster. That helps to draw insights from big data sets without having to script complex programs in say Java or Python.
- It allows distributed algorithm runs on Hadoop HDFS cluster
- It allows using different file formats such as SAS7BAT files or complex files in tab or comma delimited making data munging easier
- It provides scalable solutions by allowing users to re-use R scripts and distributing the computing over nodes through RHadoop
- When I reviewed the product - release D, at that time, "decision forest algorithm" was not available.
- The tool needs to be more integrated with other data infrastructure tools such as Teradata, Informatica etc. as well as may be with new Hadoop distribution platforms such as Cloudera or Hortonworks so the users don't have to install the tool from scratch
- I would also like to see improved capability around GUI and integration with other ecosystem. As the Big Data ecosystem would evolve in next 2-3 years, I would like to see Rev-R becoming more compatible with start-ups as well.