#1 most frequent
United States of America
45.4%184 installations of 405
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.
Categories & Use Cases
Videos
Top Performing Features
Connect to Multiple Data Sources
Ability to connect to a wide variety of data sources including data lakes or data warehouses for data ingestion
Category average: 8.8
Extend Existing Data Sources
Use R or Python to create custom connectors for any APIs or databases
Category average: 8.9
Built-in Processors
Library of processors for data quality checks
Category average: 9
Areas for Improvement
Flexible Model Publishing Options
Publish models as REST APIs, hosted interactive web apps or as scheduled jobs for generating reports or running ETL tasks.
Category average: 9.2
Security, Governance, and Cost Controls
Built-in controls to mitigate compliance and audit risk with user activity tracking
Category average: 8.6
Data Transformations
Use visual tools for standard transformations
Category average: 9.1
Who Buys & Uses RapidMiner
#2 most frequent
Germany
4.7%19 installations of 405
#3 most frequent
Canada
4.4%18 installations of 405
Very user-friendly ETL with mining capabilities. Will save you a lot of time with your data.
Pros
- 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.
Cons
- 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.
Return on Investment
- Very high positive impact because it's very fast to work with data with no coding need. You save a lot of time.
Alternatives Considered
KNIME Analytics Platform, Pentaho and SQL Server Business Intelligence Manager
Other Software Used
TIBCO Spotfire, KNIME Analytics Platform, Pentaho
Usability
Data Analytics for Marketing—yes, it can be done
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.
Cons
- Basic data cleaning is always a problem that RapidMiner might solve, but I am not aware of it.
Return on Investment
- We saved over $100k on our direct mail program by not mailing to those unlikely to respond to our mailings based on our predictive analysis.
- Our CX team has saved countless hours by automating call scripts to isolate key phrases and code each call.
Alternatives Considered
Tableau Desktop, Google Data Studio and Microsoft Power BI
Other Software Used
Microsoft 365 Business, OneNote, Trello
RapidMiner Studio: Great Training Tool and Data Compiler
Use Cases and Deployment Scope
We use RapidMinerStudio as a data organizational tool. We feed our data into RapidMiner Studio and it helps us create different data trees to sort through the massive amounts of data that we work on in a daily basis. It is very useful as a training toll to familiarize our new hires with the data that we are working with.
Pros
- Uploading data.
- Has the code we need.
- User friendly.
Cons
- User interface could be a little more fluid.
- Interfacing with other programs.
- Processing speeds.
Most Important Features
- The amount of data it can interpret.
- User-friendly.
- Easy support.
Return on Investment
- Helped with training.
- Fewer individuals working on data.
- Had to purchase expensive processing computers.
Alternatives Considered
Tableau CRM (formerly Einstein Analytics)
Other Software Used
Tableau CRM (formerly Einstein Analytics), Tableau Desktop, Asana, Microsoft Teams, Skype, Pulse Secure Unified Client, Zscaler Private Access, Cisco Secure Access by Duo
RapidMiner as Educational Data Mining Tool
Pros
- 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.
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.
Return on Investment
- As an educator, I do not seek a monetary return on any investment. What we seek as a lecturer is by looking into the outcomes like greater student learning, higher grades, or an increased number of students enrolment. Since RapidMiner is FREE for education, the first outcome I see is RapidMIner has enhanced learning and teaching analytics. Students become excited to learn analytics because they have the opportunity to use RapidMiner which is known to them as an expensive global brand and sophisticated tool.
- The second outcome is time spent to learn using an analytic tool become shorter compared to the previous platform. Therefore, we can learn more about other aspects of data analytics rather than focusing on how to use a tool.
- The third outcome is the program reputation. According to a study conducted by Maureen A. Conard, Sacred Heart University, has found that two variables, large percentage of graduates in successful careers and up-to-date technological facilities, were rated as very likely to be associated with very good academic reputation. RapidMiner is a Leader in the 2018 Gartner Magic Quadrant for Data Science and Machine Learning Platforms. Therefore, associating our academic program with the international brand like RapidMiner has enhanced our academic program reputation.
Other Software Used
Tableau Desktop
Data admirer's playroom - RapidMiner Studio
Pros
- 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
Cons
- 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
Return on Investment
- From an organization's point of view, we have been able to deliver better and quicker solutions. Thus saving a lot of time and investing in other projects.
Alternatives Considered
KNIME Analytics Platform and Alteryx Analytics
Other Software Used
Microsoft Power BI, Talend Data Integration, MapR