Likelihood to Recommend RapidMiner is really fantastic to perform fast ETL processes and work on your data as you want, no matter what is the source. You will really save a lot of time when you learn how to use it. You can create mining analysis with several algorithms, and thanks to add-ons, you can apply a lot of techniques. It will not replace a business intelligence dashboard but it allows to create great datamarts for your BI tools. One negative thing is that It's no easy to share your outputs.
Read full review We are the judgement that Wolfram Mathematica is despite many critics based on the paradigms selected a mark in the fields of the markets for computations of all kind. Wolfram Mathematica is even a choice in fields where other bolide systems reign most of the market. Wolfram Mathematica offers rich flexibility and internally standardizes the right methodologies for his user community. Wolfram Mathematica is not cheap and in need of a hard an long learner journey. That makes it weak in comparison with of-the-shelf-solution packages or even other programming languages. But for systematization of methods Wolfram Mathematica is far in front of almost all the other. Scientist and interested people are able to develop themself further and Wolfram Matheamatica users are a human variant for themself. The reach out for modern mathematics based science is deep and a unique unified framework makes the whole field of mathematics accessable comparable to the brain of Albert Einstein. The paradigms incorporated are the most efficients and consist in assembly on the market. The mathematics is covering and fullfills not just education requirements but the demands and needs of experts.
Mathematica is incompatible with other systems for mCAx and therefore the borders between the systems are hard to overcome. Wolfram Mathematica should be consider one of the more open systems because other code can be imported and run but on the export side it is rathe incompatible by design purposes. A better standard for all that might solve the crisis but there is none in sight. Selection of knowledge of what works will be in the future even more focussed and general system might be one the lossy side. Knowledge of esthetics of what will be in the highest demand in necessary and Wolfram is not a leader in this field of science. Mathematics leves from gathering problems from application fields and less from the glory of itself and the formalization of this.
Steffen Jäschke Projektspezialist bei Steffen Jäschke EinzUnt Physik, Berechnungen
Read full review Pros I am very impressed at how easily you can work within RapidMiner without much data analytics training. Plus with the help of the crowd, you can see what steps others have taken with their data analytics projects. Text mining was simple and clean. We used this for our call transcription problem where we didn't have the resources to listen to each call. We needed to qualify each call based on some key phrases. Our direct mail program was large and not very targeted. Using RapidMiner, we were able to isolate a predictive level we felt comfortable with and decided not to send to anyone below that level. We saved quite a bit of money. Read full review It allows straightforward integration of analytic analysis of algebraic expressions and their numerical implemented. Supports varying programmatic paradigms, so one can choose what best fits the problem or task: pure functions, procedural programming, list processing, and even (with a bit of setup) object-oriented programming. The extensive and rich tools for graphical rendering make it very easy to not just get 2D and 3D renderings of final output, but also to do quick-and-dirty 2D and 3D rendering of intermediate results and/or debugging results. Read full review Cons I hope RapidMiner would be the first data science platform that allows data scientists to change the behaviour of a machine learning algorithm that already exists in the repository. For example, I want to be able to change the way a genetic algorithm mutates. Automatic programming: One day, I hope RapidMiner can automatically generate codes in any 4th generation programming language based on the developed model. More tutorials/samples needed: Why doesn't RapidMiner becomes the next 'UC Irvine Machine Learning Repository'? Provide real examples and real cases for users to study and understand the best practices in modelling. RapidMiner already has some datasets for a tutorial. Besides the existing samples, I hope RapidMiner can provide more sample data and examples. Read full review Should include more libraries and functions. Should include more functions that can be used in Machine Learning. Should include more functions that can be used in Data Science. Read full review Likelihood to Renew Very fast and user-friendly tool
Read full review Usability Very use to use and learn
Read full review Support Rating Wolfram Mathematica is a nice software package. It has very nice features and easy to install and use in your machine. Besides this, there is a nice support from Wolfram. They come to the university frequently to give seminars in Mathematica. I think this is the best thing they are doing. That is very helpful for graduate and undergraduate students who are using Mathematica in their research.
Read full review Alternatives Considered We tried different data tools and we figured we give RapidMinder Studio a shot as one of our employees had experience with it, and when compared to some of the other tools that we used it was the best fit among the test group that we used. Overall it was a little more fluid and user-friendly.
Read full review We have evaluated and are using in some cases the Python language in concert with the Jupyter notebook interface. For UI, we using libraries like React to create visually stunning visualizations of such models. Mathematica compares favorably to this alternative in terms of speed of development. Mathematica compares unfavorably to this alternative in terms of license costs.
Read full review Return on Investment Thanks to the patters that RapidMiner has detected, we have been able to follow clues in the right direction, both for the Protein Interaction Network Analysis and for the Epilepsy Research Students and participants of the machine learning workshops have learned about this technology and about the tool Read full review Easy to solve huge mathematical equations, so it saved time there Doing analysis and plotting graphs is also another plus point Learning is very slow, and it took lot of time to learn its scripting language Read full review ScreenShots