The DataRobot AI Platform is presented as a solution that accelerates and democratizes data science by automating the end-to-end journey from data to value and allows users to deploy AI applications at scale. DataRobot provides a centrally governed platform that gives users AI to drive business outcomes, that is available on the user's cloud platform-of-choice, on-premise, or as a fully-managed service. The solutions include tools providing data preparation enabling users to explore and…
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Microsoft R Open / Revolution R Enterprise
Score 8.9 out of 10
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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.
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Pricing
DataRobot
Microsoft R Open / Revolution R Enterprise
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
DataRobot
Microsoft R Open / Revolution R Enterprise
Free Trial
Yes
No
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
DataRobot
Microsoft R Open / Revolution R Enterprise
Features
DataRobot
Microsoft R Open / Revolution R Enterprise
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
DataRobot
-
Ratings
Microsoft R Open / Revolution R Enterprise
5.3
Ratings
45% below category average
Connect to Multiple Data Sources
00 Ratings
6.10 Ratings
Extend Existing Data Sources
00 Ratings
6.00 Ratings
Automatic Data Format Detection
00 Ratings
6.00 Ratings
MDM Integration
00 Ratings
3.00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
DataRobot
-
Ratings
Microsoft R Open / Revolution R Enterprise
7.0
Ratings
18% below category average
Visualization
00 Ratings
7.00 Ratings
Interactive Data Analysis
00 Ratings
7.00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
DataRobot
-
Ratings
Microsoft R Open / Revolution R Enterprise
4.8
Ratings
52% below category average
Interactive Data Cleaning and Enrichment
00 Ratings
5.10 Ratings
Data Transformations
00 Ratings
5.00 Ratings
Data Encryption
00 Ratings
3.00 Ratings
Built-in Processors
00 Ratings
6.00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
DataRobot
-
Ratings
Microsoft R Open / Revolution R Enterprise
6.0
Ratings
33% below category average
Multiple Model Development Languages and Tools
00 Ratings
5.00 Ratings
Automated Machine Learning
00 Ratings
5.00 Ratings
Single platform for multiple model development
00 Ratings
8.00 Ratings
Self-Service Model Delivery
00 Ratings
6.00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
DataRobot can be used for risk assessment, such as predicting the likelihood of loan default. It can handle both classification and regression tasks effectively. It relies on historical data for model training. If you have limited historical data or the data quality is poor, it may not be the best choice as it requires a sufficient amount of high-quality data for accurate model building.
Revolution Analytics is a very compelling product for Big Data Analytics. It allows distributed computing over multiple hadoop nodes thus allowing HDFS to do its role cleanly i.e. cheap massive storage and it does good job of running algorithms using R or similar programming language on Hadoop. It would be definitely advantage for the organization who uses either R or SAS as their statistical model development tool as Rev-R support both the platforms. Overall, very positive experience with Rev-R.
Further improvements to their text analysis tool, to be more like the Qualtrics text analysis tool, would be a great addition. Qualtrics has templates built into their text analysis tool for customer service, quality control, etc, and will automatically slot your text responses into categories associated with certain sub areas of those larger categories.
DataRobot presents a machine-learning platform designed by data scientists from an array of backgrounds, to construct and develop precise predictive modeling in a fraction of the time previously taken. The tech invloved addresses the critical shortage of data scientists by changing the speed and economics of predictive analytics. DataRobot utilizes parallel processing to evaluate models in R, Python, Spark MLlib, H2O and other open source databases. It searches for possible permutations and algorithms, features, transformation, processes, steps and tuning to yield the best models for the dataset and predictive goal.
In general, Revolution Analytics brings a lot of value to the organization. The renewal decision would be based on return on investment in terms of quantified actionable insights that are getting generated against the cost of the product. Additionally, market brand of the tool and reputation risk in terms of possible acquisition and its impact to overall organizational analytic strategy would be considered as well.
It is good, easy to use, improvements are being made to the product and more info being shared in the community. It just needs some more time to become more integrated to other platforms and tools/data out there.
As I am writing this report I am participating with Datarobot Engineers in an complex environment and we have their whole support. We are in Mexico and is not common to have this commitment from companies without expensive contract services. Installing is on premise and the client does not want us to take control and they, the client, is also limited because of internal IT regulations ,,, soo we are just doing magic and everybody is committed.
Generally support comes through the forums and user generated channels which are helpful, easy to access, quickly turned around and provided by knowledgeable users. However the support channels are not employees and the channels are often used as a way to learn quick difficult elements of R. Better design, users interface and tutorial options would alleviate the need for this sort of interaction.
I've done machine learning through python before, however having to code and test each model individually was very time consuming and required a lot of expertise. The data Robot approach, is an excellent way of getting to a well placed starting point. You can then pick up the model from there and fine tune further if you need.
R is decent for our needs but in the end didn't quite solve all of our needs so moved on. It is a good tool so far. its been a couple months since we last touched it so with changes continuing and more wide spread use and more info being published this tool will improve. Depending upon your needs this can be very easy for you to setup, use, and maintain when compared to other tools out there. My suggestion is to ensure you fully understand your use cases first with data sources identified to ensure this tool can meet your needs.