We performed a comparison between RapidMiner and Tableau based on real PeerSpot user reviews.
Find out what your peers are saying about Alteryx, RapidMiner, SAP and others in Predictive Analytics."I like not having to write all solutions from code. Being able to drag and drop controls, enables me to focus on building the best model, without needing to search for syntax errors or extra libraries."
"The best part of RapidMiner is efficiency."
"The solution is stable."
"It is easy to use and has a huge community that I can rely on for help. Moreover, it is interactive."
"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 most valuable features are the Binary classification and Auto Model."
"The most valuable feature of RapidMiner is that it is code free. It is similar to playing with Lego pieces and executing after you are finished to see the results. Additionally, it is easy to use and has interesting utilities when preparing the data. It has a utility to automatically launch a series of models and show the comparisons. When finished with the comparisons you can select the best one, and deploy it automatically."
"The GUI capabilities of the solution are excellent. Their Auto ML model provides for even non-coder data scientists to deploy a model."
"It most valuable feature is its ease of developing visualizations, not just charts and graphs."
"Show Me is a feature to help with knowing which chart is an appropriate one for the selected variables, and it makes helps in creating appropriate visuals."
"Tableau has greatly enhanced our organization's data-driven decision-making processes by enabling us to create visually compelling reports and dashboards."
"The product offers an intuitive user interface, detailed screens and widgets, and the absence of data limitations"
"It has a shallow learning curve and so you can go to market very, very, very quickly."
"Easy to create graphs and visualizations."
"It's a very good, flexible product, and it's easy to learn."
"It's very user-friendly. It's not like Power BI, Tableau is very user-friendly. Anybody can use Tableau. It's very easy to adopt things. I can visualize the stats."
"RapidMiner can improve deep learning by enhancing the features."
"It would be helpful to have some tutorials on communicating with Python."
"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."
"In terms of the UI and SaaS, the user interface with KNIME is more appealing than RapidMiner."
"I would like to see all users have access to all of the deep learning models, and that they can be used easily."
"RapidMiner isn't cheap. It's a complete solution, but it's costly."
"I would like to see more integration capabilities."
"In the Mexican or Latin American market, it's kind of pricey."
"In the next release, I would like to be able to have the option to see more raw data that I'm converting on the dashboard."
"I have used Power BI as well as Tableau. There are a couple of interesting features that I like in Power BI, but they are not present in Tableau. For example, in Power BI, if I am looking at country-wise population, I can type and ask for the country that has the maximum population, and it will automatically give an answer and address that query. This kind of feature is not there in Tableau. Similarly, in Power BI, for integrating with the latest ML algorithms, we have decision trees and primarily multiple machine learning algorithms. The decision tree essentially visualizes the patterns in the data. We don't have such a feature in Tableau. If Tableau can integrate with the machine learning algorithms and help us to do visualizations, it would be a wonderful combination. Most of the people are going for Tableau primarily for visualization purposes. However, in the data science industry, users want to do model building as well as tell a story. As of now, Tableau is fulfilling the requirements for visualization purposes. If they can bring it up to a level where I can use it for machine learning purposes as well as for visualization, it would be very helpful. Many people who want to do data science don't want to write a code. Tableau is anyway a drag and drop tool, and if they can provide those options as well, it will be a powerful combination."
"What is happening, with so many tools coming up in the market, is that people have to continuously get educated in order to use some of the more advanced features."
"Most of the problems in Tableau Online that I have noticed have to do with performance or weird, inexplicable bugs that I can't pin down. For example, you might try unloading some data, and you'll be waiting for a long time without anything happening."
"People are migrating to Microsoft BI due to the speed, which is quite slow to load, and the lack of visualization options."
"Tableau has so many functions, so sometimes it's hard to find the right solution quickly. I have to search multiple menu bars to find the right command."
"Improvements can be made in template support. The workbook file structure is really hard to version control. If there was some sort of version control support offered particularly for workbooks, that would help big time."
"The customization requires a lot of effort and should be simplified. The performance could be better."
RapidMiner is ranked 2nd in Predictive Analytics with 19 reviews while Tableau is ranked 2nd in BI (Business Intelligence) Tools with 290 reviews. RapidMiner is rated 8.6, while Tableau is rated 8.4. 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". On the other hand, the top reviewer of Tableau writes "Provides fast data access with in-memory extracts, makes it easy to create visualizations, and saves time". RapidMiner is most compared with KNIME, Alteryx, Dataiku Data Science Studio, Microsoft Azure Machine Learning Studio and IBM SPSS Modeler, whereas Tableau is most compared with Microsoft Power BI, Amazon QuickSight, Domo, SAS Visual Analytics and Databricks.
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.
