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RapidMiner

RapidMiner

Overview

What is RapidMiner?

RapidMiner is a data science and data mining platform, from Altair since the late 2022 acquisition. RapidMiner offers full automation for non-coding domain experts, an integrated JupyterLab environment for seasoned data scientists, and a visual drag-and-drop designer. RapidMiner’s project-based…

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Recent Reviews

TrustRadius Insights

RapidMiner Studio has been widely utilized across various industries for a range of use cases. Users have found success in using …
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Awards

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Pricing

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Professional

$7,500.00

Cloud
Per User Per Month

Enterprise

$15,000.00

Cloud
Per User Per Month

AI Hub

$54,000.00

Cloud
Per User Per Month

Entry-level set up fee?

  • No setup fee
For the latest information on pricing, visithttps://rapidminer.com/pricing

Offerings

  • Free Trial
  • Free/Freemium Version
  • Premium Consulting/Integration Services
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Product Demos

RapidMiner Platform Demo: Part 1 - Getting Started with RapidMiner 7.3

YouTube
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Product Details

What is RapidMiner?

RapidMiner is a data science and data mining platform, from Altair since the late 2022 acquisition. RapidMiner offers full automation for non-coding domain experts, an integrated JupyterLab environment for seasoned data scientists, and a visual drag-and-drop designer. RapidMiner’s project-based framework helps to ensure that others can build off their work using visual workflows or automated data science.

RapidMiner Videos

RapidMiner in Action
RapidMiner and OSI Demo
Walk-Through of RapidMiner AI Hub (Formerly RapidMiner Server)
Automated Data Science - Data Preparation in DataMiner

RapidMiner Technical Details

Deployment TypesSoftware as a Service (SaaS), Cloud, or Web-Based
Operating SystemsUnspecified
Mobile ApplicationNo
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Comparisons

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Reviews and Ratings

(57)

Community Insights

TrustRadius Insights are summaries of user sentiment data from TrustRadius reviews and, when necessary, 3rd-party data sources. Have feedback on this content? Let us know!

RapidMiner Studio has been widely utilized across various industries for a range of use cases. Users have found success in using RapidMiner Studio to create ETL processes for loading BI datamarts with data from operational databases. Additionally, the software has been instrumental in performing data mining tasks such as text processing, image processing, and algorithm data analysis.

Marketing teams have leveraged RapidMiner Studio for predictive analytics in direct mail programs and text mining for call transcripts. The software has also served as a central data science platform for teaching data analytics and machine learning, providing an essential tool for educational purposes. Furthermore, RapidMiner Studio has demonstrated its versatility by being used for real-world analyses in healthcare, retail, manufacturing, and BFSI sectors.

Companies like Aptus Data Labs rely heavily on RapidMiner Studio to deliver their solutions efficiently. The software has proven valuable for fraud analysis in banking and financial industries, claim and travel analytics in manufacturing, and text mining in pharmaceutical firms. Individual analysts have also found success using RapidMiner Studio for analysis and predictive modeling of student-related data.

In addition to these use cases, RapidMiner Studio has been applied to build and test energy usage models for buildings. Risk coverage providers like DisperSurance have utilized the software for optimization, automation, fraud detection, and determining profitable e-commerce strategies. It has also been instrumental in processing data from clients in telecom and banking industries while assisting in modeling machine learning structures.

Moreover, RapidMiner Studio has served as a powerful data organizational tool by enabling users to sort through massive amounts of data and run statistical algorithms efficiently. It has been effectively employed for client churning analysis, client and banker clustering, and market basket analysis. Sales and marketing teams have benefited from its predictive analytics capabilities using CRM data.

The software's versatility extends even further with applications in pattern finding in epilepsy clinical data, protein interaction networks analysis, and gaining insights about various datasets. RapidMiner Studio offers a wide range of machine learning algorithms, making it suitable for text mining, data analysis, and machine learning tasks. Its diverse applications and user-friendly interface have made it a valuable tool for users across industries.

Intuitive User Interface: Several users have praised RapidMiner Studio for its intuitive user interface, which has made it easy for them to learn and navigate the software. The intuitive workflow paradigm has allowed users to quickly grasp the functionality of the software and perform tasks with ease.

Versatile Operators: Many reviewers have highlighted the versatility and power of RapidMiner Studio's operators. These operators are complete and powerful, especially in handling tasks such as data preprocessing, data visualization, and data mining analytics. Users have found these operators to be valuable tools in various areas of analysis.

Extensive Support System: Numerous users have commended RapidMiner Studio for its excellent documentation, countless worked examples, and large user community that provides training support. This extensive support system has been highly valued by users as it offers valuable resources for learning and troubleshooting, ensuring effective utilization of the software's capabilities.

Outdated User Interface: Several users have expressed dissatisfaction with RapidMiner's user interface, stating that it is outdated and not up to the standards of other software like Office or Microsoft.

Difficulties in Finding Key Operators: Some users have reported difficulties in finding key operators within RapidMiner's interface, which has caused frustration and hindered their workflow.

Lack of Documentation for Operators: Many reviewers have mentioned that there is a lack of documentation for several operators in RapidMiner. This makes it challenging for users to understand the impact of these operators on their analysis, leading to confusion and inefficiency.

Users of RapidMiner have provided several recommendations based on their experiences with the tool. The three most common recommendations are as follows:

  1. Provide more support for finding mining algorithms and add Indonesian language support: Many users suggest that RapidMiner should make it easier to locate mining algorithms within the application. Additionally, they recommend adding support for the Indonesian language to cater to a wider audience.

  2. Utilize RapidMiner for various data analysis purposes: Users highly recommend using RapidMiner for different data mining and analysis tasks, including predictive analysis and marketing purposes. They find the tool user-friendly and effective in developing prediction models.

  3. Take advantage of RapidMiner's features and resources: Users recommend exploring RapidMiner's Auto-ML feature, which they consider a significant advancement. They also suggest accessing the extensive training material provided by RapidMiner, taking online classes, and working on hands-on tutorials to gain a competitive edge. Additionally, they emphasize the importance of engaging with sales representatives and utilizing the continuous updates from the pro-active team.

Overall, users find RapidMiner to be an excellent tool for data mining and analysis, particularly for implementing complex machine learning algorithms and improving dataset analysis. They appreciate its wide range of machine learning algorithms, powerful ETL operations, interactive visualizations, and great online support. However, some users suggest improvements such as adding Korean language support and expanding popularity in business settings.

Attribute Ratings

Reviews

(1-18 of 18)
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David Baltar Boilève | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Incentivized
  • RapidMiner is really fast at reading all kinds of databases. We read and merge databases like SQL Server, Informix, MySQL, and Oracle. Configuring access is easy, some drivers are inbuilt, but it's not difficult to find new java drivers to allow RapidMiner to connect to other databases.
  • Performing all kinds of transformations, calculations (date, percentages...), joins, and filters without coding. We have several different databases and this makes my life a lot easier. Knowing that this part is 80% of analyst work, you know that you can work more on the analyses itself and not on cleaning and preparing data.
  • You can clone transformations to reuse on new analyses, so you save a lot of time. There's a lot of add-ons to make different things (text, image analysis, recommender systems, etc).
  • Training is easy, the tool is intuitive and there's a lot of videos on the internet. The community is very active.
  • Sharing RapidMiner Studio analysis is not easy. You may think that the RapidMiner Server does that work but no. It's more automated job oriented or useful to run models on a web site. If you need to use it for Business Analytics dashboards, this is not the tool. It's more a backstage tool for analyst. Some charts are good but other not so much.
  • The free edition allows you to work with 10,000 rows, but if you need more, it's not cheap (100,000 rows - 2,500 USD/year, 1,000,000 rows - 5,000 USD/year).
  • The commercial team is not very reactive. I've asked for a RapidMiner Education Program and Rapidminer Server quotation with no answer. I guess that's because they were changing from an opensource company model to a more commercial one.
Sue Bennett | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Incentivized
  • 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.
  • Basic data cleaning is always a problem that RapidMiner might solve, but I am not aware of it.
Mohd Zakree Ahmad Nazri | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
  • The RapidMiner provides a rich set of Machine Learning algorithms for Data Mining tasks, along with a comprehensive set of operators (functions) for data pre-processing. RapidMiner has a repository containing hundreds of machine learning algorithms and functions.
  • RapidMiner is easy to use because RapidMiner is a user-friendly visual workflow designer software. Visualization of the process really helps users with data preparation and modelling. It makes my job easier in teaching machine learning and predictive analytics because I can show them the role of each operator and which one is vital in getting the right model. Students can directly see and understand the effect of using specific algorithms and functions after a few clicks, drags and drops. RapidMiner is something quick and easy to master.
  • It is FREE! RapidMiner is available for free for educational use. I have been using RapidMiner for about three years, and I have never encountered any problem in renewing my license. The Educational Program License lasts for a year. My students have never complained about RapidMiner as the customer support is very efficient.
  • RapidMiner Marketplace: If there are 'missing algorithm' from the RapidMiner library, we always can install extensions from the RapidMiner Marketplace. For example, I can access an extra about 100 additional modelling schemes after installing the WEKA extension. What ever the tasks are, if the required algorithm or functions are not available in the RapidMiner repository of ML algorithms, I can always find it in the marketplace.
  • 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.
Score 9 out of 10
Vetted Review
Verified User
Incentivized
  • No need to script anything, and still doing modeling is amazing
  • Easy to use by just dragging and dropping operators
  • Can use the tool for data cleaning, data analysis, data modeling
  • Wish the tool was more efficient in terms of processing power. The tool takes a lot of CPU processing power, even for a small process on a small data set
  • Wish there were more options on charts and graphs to visualize the data
Mauricio Quiroga-Pascal Ortega | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
  • RapidMiner has a very large ML algorithms library and excellent tools for automated optimization of those algorithms.
  • Is one of the best tools I know for text mining and analytics. It’s not only very powerful but also very intuitive and easy to use.
  • Since it’s is very easy to pass from design to production, it’s an excellent tool for building and testing complete models.
  • It should improve it friendliness with using multimedia (video, pictures, audio). For instance, is not easy to connect between raw audio and its related text data for analytics.
  • It also should improve it interface design and intuitiveness. Its design isn’t very motivational and sometimes it’s hard to find some key operators.
  • It should improve the capabilities to integrate RapidMiner to third party applications.
Cyril Joudieh | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Incentivized
  • Build a model
  • Validate a model
  • See how accurate our predictions are
  • We prefer to use our own coding to clean the data since we use huge databases using MySQL, Oracle or MS-SQL
  • We use the visualization tools of RapidMiner to analyze the data
  • The graphics of the charts needs some work. Sometimes it is hard to read on high resolution screens
  • Sometimes it is hard to find the operators
  • The interface is far from the standards of Office or Microsoft in general.
Score 10 out of 10
Vetted Review
Verified User
Incentivized
  • Easy to use. The Graphic User Interface allows users to build their models very fast and very intuitively
  • Fast to learn. There are plenty online resources (official and unofficial) to learn how to use RapidMiner
  • Multiple Tools. RapidMiner has several tools to help with the machine learning activity that a person is doing, different models, importing, etc.
  • Export. It would be great to be able to export the resulting data, graphs and models in an easier way. Currently I find that not intuitive enough.
  • It would be wonderful (not sure if it fits the company business model) to have an API access, so people would be able to integrate some of RapidMiner functionalities inside their applications
Sheetal Sahu | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
ResellerIncentivized
  • A great tool to start exploring data science and machine learning. Its intuitive GUI, tutorials, help window, sample processes, and recommendations make it the best place to learn and expand your knowledge horizon.
  • RapidMiner is an expert in building end to end solutions. Creating a process in the studio and then running it in production using the server is easy and fast. And also using web services, we can integrate the solution into an organization's in-house application or create a new web application in RapidMiner server. This makes solution delivery faster compared to R and Python.
  • Text mining and analytics capability in RapidMiner. I think text processing is very easy here. Using Rosette and deep learning extensions, I have delivered such great solutions.
  • Smart Automations like automatically identifying parameter values, auto model and turbo prep etc. saves a lot of time and provide better results
  • RapidMiner Server- It is very basic in terms of appearance. Web Apps can be improved by providing default themes and it needs a lot more features to be added.
  • Multi-process window in RapidMiner Studio. Multiple design view can be added for switching between processes and model building can be made easier.
  • Git Integration for version control. We have something called MyExperiment in RapidMiner but it is far from Git. But if we could have git integration, multiple users can work on the same process and this version control can help to refer previous solutions as well.
  • Graphs in RapidMiner Studio are a bit old fashioned
Score 8 out of 10
Vetted Review
Verified User
Incentivized
  • Ease of use in the user interface
  • Multiple predictive analytic models to address any needs
  • Compatibility with other existing software platforms to allow for better data integration
  • As the company has grown, support has been a challenge at times. A better response time would be nice.
Rebecca T Barber, MBA, PHD | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
  • Work-flow visualization - the interface allows you to clearly see what the steps are and where any failures occur
  • Keeping up to date with the latest algorithms and improving the performance of those algorithms
  • Extensions that allow linking up to many of the other top tools
  • Some of the error messages are vague enough to confuse end users
  • Certain terminology used by the tool can confuse a new user
  • There are a lot of available options, many of which have only minimal documentation available. Better documentation of not just what the option is but how it might impact an analysis would help.
Danushka Bandara | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Incentivized
  • Rapid prototyping of machine learning models.
  • Provides predefined parameters that are crowd sourced and provide helpful parameter ranges.
  • The interface is very easy to use, even for someone with no coding experience.
  • Provide model exportability.
  • We have had trouble exporting the models to languages like php.
  • The ability to build custom models would be useful, using scripting languages.
  • Ability to automate running the machine learning for multiple tasks would be useful.
Jim Kitzmiller | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Incentivized
  • The hands-on tutorials provide an understandable step-by-step to being able to provide simple solutions to complex problems.
  • RapidMiner provides near instant statistics and quick graphs giving you an overview of your data. This saves a lot of time and complexity.
  • Provides a simple drag and drop means to solve complex data science problems.
  • There are a few places where the documentation for the tutorials differ from the way that RapidMiner actually works.
  • Several times the webinar presenter didn't show up.
Score 10 out of 10
Vetted Review
Verified User
Incentivized
  • RapidMiner Studio offers a superb user interface with an intuitive workflow paradigm that is very easy to learn.
  • RapidMiner Studio’s operators make it a complete and powerful tool for data preprocessing, data visualization, and data mining/analytics.
  • RapidMiner Studio provides excellent documentation, countless worked examples, training and support via a large user community.
  • Every problem is solved using a sequence of operators.
  • Statistical analysis capabilities offered with the T-Test, ANOVA, Grouped ANOVA, and ANOVA Matrix operators.
  • Textual data mining operators.
  • Web-based and cloud computing capabilities.
  • Visualization capabilities.
  • Marketplace Extensions – especially Finance And Economics.
  • Process portability.
  • With large-sized data sets, there are processing speed issues with a few of the operators. However, RapidMiner Studio 7.4 contains several new performance enhancing features.
Kamesh Emani | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Incentivized
  • Data Cleaning & Transformation
  • Data Modeling (Algorithm Implementation)
  • Data Visualization
  • Data Integration
  • Data Visualization can be improved. I have used Tableau which has more colorful schema for graphs. If rapidminer improves its graphs look it would be great.
  • If connectivity to Hadoop HDFS is provided that would be great.
  • If more examples would have been added for each block it would be good. Maybe not in the IDE but like videos on the website. I could find videos for some but not for every block.
Score 7 out of 10
Vetted Review
Verified User
Incentivized
  • If you have people on your team that are new to analytics and do not have programming experience in Sas, R or Python, RapidMiner is the way to go.
  • The module based approach of RapidMiner is very useful, they have a heavy community support and one of my favorite features is the suggestions they give by telling you that such and such step was the most common one used after a transformation or an import etc...
  • RapidMiner is great for people with no programming experience but I have found that certain tasks that would normally take very little code to do can often become very convoluted with RapidMiner. I am talking about tasks like filtering and subsetting and other transformation type tasks.
August 03, 2016

RapidMiner Studio

Score 8 out of 10
Vetted Review
Verified User
Incentivized
  • Great GUI. Very easy to use.
  • Lot of inbuilt machine learning algorithms.
  • The free version also has most of the things that may be required on a day to day basis.
  • The integration between RapidMiner and R isn't perfect as yet.
  • Less number of statistical methods.
  • A lot of operators present.
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