Frontline Systems Analytic Solver is an Excel add-on for performing data mining, and predictive analytics from within Microsoft Excel.
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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
Analytic Solver
Microsoft R Open / Revolution R Enterprise
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Analytic Solver
Microsoft R Open / Revolution R Enterprise
Free Trial
No
No
Free/Freemium Version
No
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
Analytic Solver
Microsoft R Open / Revolution R Enterprise
Features
Analytic Solver
Microsoft R Open / Revolution R Enterprise
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Analytic Solver
-
Ratings
Microsoft R Open / Revolution R Enterprise
5.3
3 Ratings
45% below category average
Connect to Multiple Data Sources
00 Ratings
6.13 Ratings
Extend Existing Data Sources
00 Ratings
6.03 Ratings
Automatic Data Format Detection
00 Ratings
6.03 Ratings
MDM Integration
00 Ratings
3.01 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Analytic Solver
-
Ratings
Microsoft R Open / Revolution R Enterprise
7.0
3 Ratings
18% below category average
Visualization
00 Ratings
7.03 Ratings
Interactive Data Analysis
00 Ratings
7.03 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Analytic Solver
-
Ratings
Microsoft R Open / Revolution R Enterprise
4.8
3 Ratings
52% below category average
Interactive Data Cleaning and Enrichment
00 Ratings
5.13 Ratings
Data Transformations
00 Ratings
5.03 Ratings
Data Encryption
00 Ratings
3.01 Ratings
Built-in Processors
00 Ratings
6.03 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Analytic Solver
-
Ratings
Microsoft R Open / Revolution R Enterprise
6.0
3 Ratings
33% below category average
Multiple Model Development Languages and Tools
00 Ratings
5.03 Ratings
Automated Machine Learning
00 Ratings
5.02 Ratings
Single platform for multiple model development
00 Ratings
8.03 Ratings
Self-Service Model Delivery
00 Ratings
6.03 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Based on my limited experience and use, and therefore limited global knowledge of the software, I would recommend it especially if the data that will be used as inputs to the model has previously worked on a spreadsheet such as Excel. I would also recommend it to analyze problems of medium and small size. Given the experience I have had when I have used it with large problems, there have been noticeable decreases in the speed of response (which are not associated with the size of the system of equations involved in the calculation). Excellent for processing linear programming models.
If you are a MS shop specifically, or have more generic data requirement needs from Microsoft sourced data this will work well. If you have a lot of disparate data across a number of unique platforms/cloud systems/3rd party hosted data warehouses then this product will have issues or a lack of documentation on the net. Performance-wise this product is equal to other R platforms out there.
On the few occasions when I have used it to deal with problems of optimization of relatively large parameters (with a large number of restrictions and decision variables), the program has been slower, not substantially but slower, than programs such as the WinQsb, even when the latter runs on 32-bit machines and not 64. That has caught my attention, even though it is not a real problem for the uses I give to the program.
Given my partial function as a university professor, it has been much more effective and practical to use other software, due to the limited options that the educational license associated with the software has.
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.
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.
We believe in building the models in Excel. A limitation with Excel is that Excel Solver can not take more than 200 decision variables with multiple constraints. It is cheap in terms of license and maintenance fees against other softwares which are available in the market.
The two are different products for different purposes. But for someone who has little or no experience in R programming, Power BI would be better for starting with. Having said that, Microsoft R is built on R, thus allowing for customization of complex calculations not typically available otherwise.
- It has allowed finding ways to optimize (minimizing costs or times) the field processes involved in various projects.
It has even allowed, in specific cases where it was used for that purpose, to optimize the allocation of resources (people) to work in different jobs that present weekly variations of the activity that these people must perform.
It has allowed the sensitivity analysis of projects to changes in the decision variables related to them, which, and in very dynamic and changing environments, resulted in substantial decreases in money losses.