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Compare IBM Predictive Analytics vs. RapidMiner

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Featured Review
Find out what your peers are saying about Alteryx, SAP, RapidMiner and others in Predictive Analytics. Updated: November 2021.
555,139 professionals have used our research since 2012.
Quotes From Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros
"The most valuable feature is the predictive capability in marketing use cases."

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"Scalability is not really a concern with RapidMiner. It scales very well and can be used in global implementations.""The most valuable features are the Binary classification and Auto Model.""The most valuable feature of RapidMiner is that it can read a large number of file formats including CSV, Excel, and in particular, SPSS.""The GUI capabilities of the solution are excellent. Their Auto ML model provides for even non-coder data scientists to deploy a model.""The most valuable feature is what the product sets out to do, which is extracting information and data.""The data science, collaboration, and IDN are very, very strong.""It's helpful if you want to make informed decisions using data. We can take the information, tease out the attributes, and label everything. It's suitable for profiling and forecasting in any industry.""RapidMiner is very easy to use."

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Cons
"Using IBM Predictive Analytics requires more skill, resources, and training than some other solutions."

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"The biggest problem, not from a platform process, but from an avoidance process, is when you work in a heavily regulated environment, like banking and finance. Whenever you make a decision or there is an output, you need to bill it as an avoidance to the investigator or to the bank audit team. If you made decisions within this machine learning model, you need to explain why you did so. It would better if you could explain your decision in terms of delivery. However, this is an issue with all ML platforms. Many companies are working heavily in this area to help figure out how to make it more explainable to the business team or the regulator.""It would be helpful to have some tutorials on communicating with Python.""I would like to see all users have access to all of the deep learning models, and that they can be used easily.""In the Mexican or Latin American market, it's kind of pricey.""A great product but confusing in some way with regard to the user interface and integration with other tools.""RapidMiner would be improved with the inclusion of more machine learning algorithms for generating time-series forecasting models.""I think that they should make deep learning models easier.""The visual interface could use something like the-drag-and-drop features which other products already support. Some additional features can make RapidMiner a better tool and maybe more competitive."

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Pricing and Cost Advice
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"Although we don't pay licensing fees because it is being used within the university, my understanding is that the cost is between $5,000 and $10,000 USD per year.""The client only has to pay the licensing costs. There are not any maintenance or hidden costs in addition to the license."

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Top Answer: It's helpful if you want to make informed decisions using data. We can take the information, tease out the attributes, and label everything. It's suitable for profiling and forecasting in any… more »
Top Answer: Many things in the interface look nice, but they aren't of much use to the operator. It already has lots of variables in there.
Ranking
5th
Views
74
Comparisons
22
Reviews
1
Average Words per Review
571
Rating
7.0
3rd
Views
7,937
Comparisons
6,269
Reviews
9
Average Words per Review
670
Rating
8.7
Comparisons
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Overview
Information Not Available

RapidMiner's unified data science platform accelerates the building of complete analytical workflows - from data prep to machine learning to model validation to deployment - in a single environment, improving efficiency and shortening the time to value for data science projects.

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Sample Customers
Getin Noble Bank S.A., North Pacific Bank Ltd., RightShip, California Franchise Tax Board, Consolidated Communications, Coherent Path Inc., Rossmann Supermarkety Drogeryjne Polska Sp. z o.o., Tennessee Highway Patrol, Banco de Prevision Social, Comptel Corp.
PayPal, Deloitte, eBay, Cisco, Miele, Volkswagen
Top Industries
No Data Available
REVIEWERS
University38%
Energy/Utilities Company13%
Educational Organization13%
Engineering Company13%
VISITORS READING REVIEWS
Comms Service Provider22%
Computer Software Company20%
University8%
Government7%
Company Size
No Data Available
REVIEWERS
Small Business57%
Midsize Enterprise14%
Large Enterprise29%
VISITORS READING REVIEWS
Small Business27%
Midsize Enterprise3%
Large Enterprise70%
Find out what your peers are saying about Alteryx, SAP, RapidMiner and others in Predictive Analytics. Updated: November 2021.
555,139 professionals have used our research since 2012.

IBM Predictive Analytics is ranked 5th in Predictive Analytics with 1 review while RapidMiner is ranked 3rd in Predictive Analytics with 9 reviews. IBM Predictive Analytics is rated 7.0, while RapidMiner is rated 8.6. The top reviewer of IBM Predictive Analytics writes "Good prediction capability for marketing purposes, although it needs to be more flexible". On the other hand, the top reviewer of RapidMiner writes "Offers good tutorials that make it easy to learn and use, with a powerful feature to compare machine learning algorithms". IBM Predictive Analytics is most compared with , whereas RapidMiner is most compared with KNIME, Alteryx, Microsoft Azure Machine Learning Studio, Dataiku Data Science Studio and DataRobot.

See our list of best Predictive Analytics vendors.

We monitor all Predictive Analytics reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.