We performed a comparison between IBM SPSS Statistics, KNIME, and RapidMiner based on real PeerSpot user reviews.
Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms."You can find a complete algorithm in the solution and use it. You don't need to write your own algorithms for predictive analytics. That's the most valuable feature and the main one we use."
"SPSS can handle whatever you throw at it, whether your data set contains 10,000, 100,000, or a million objects. It's like the heavy artillery of analytical tools."
"IBM SPSS Statistics depends on AI."
"SPSS is quite robust and quicker in terms of providing you the output."
"The solution is very comprehensive, especially compared to Minitabs, which is considered more for manufacturing. However, whatever data you want to analyze can be handled with SPSS."
"It has the ability to easily change any variable in our research."
"Since we are using the software as a statistical tool, I would say the best aspects of it are the regression and segmentation capabilities. That said, I've used it for all sorts of things."
"One feature I found very valuable was the analysis of variance (ANOVA)."
"It is a stable solution...It is a scalable solution."
"Since KNIME is a no-code platform, it is easy to work with."
"Easy to use, stable, and powerful."
"It can handle an unlimited amount of data, which is the advantage of using Knime."
"The most valuable feature is the data wrangling, which is what I mainly use it for."
"What I like most about KNIME is that it's user-friendly. It's a low-code, no-code tool, so students don't need coding knowledge. You can make use of different kinds of nodes. KNIME even has a good description of each node."
"Usability, and organising workflows in very neat manner. Controlling workflow through variables is something amazing."
"Valuable features include visual workflow creation, workflow variables (parameterisation), automatic caching of all intermediate data sets in the workflow, scheduling with the server."
"It is easy to use and has a huge community that I can rely on for help. Moreover, it is interactive."
"The GUI capabilities of the solution are excellent. Their Auto ML model provides for even non-coder data scientists to deploy a model."
"The solution is stable."
"The documentation for this solution is very good, where each operator is explained with how to use it."
"The best part of RapidMiner is efficiency."
"RapidMiner is a no-code machine learning tool. I can install it on my local machine and work with smaller datasets. It can also connect to databases, allowing me to build models directly on the data stored there. RapidMiner offers a wider range of operators than other tools like Dataiku, making it a better option for my needs."
"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."
"Scalability is not really a concern with RapidMiner. It scales very well and can be used in global implementations."
"In developing countries, it would be beneficial to provide certain features to users at no cost initially, while also customizing pricing options."
"In some cases, the product takes time to load a large dataset. They could improve this particular area."
"It could provide even more in the way of automation as there are many opportunities."
"IBM SPSS Statistics could improve the visual outputs where you are producing, for example, a graph for a company board of directors, or an advert."
"Perhaps in terms of visualization. It's not really easy to do some data visualization, just simple, descriptive analysis in SPSS. I think that could be an area for improvement."
"The solution needs to improve forecasting using time series analysis."
"Better documentation on how to use macros."
"The technical support should be improved."
"The most difficult part of the solution revolves around its areas concerning machine learning and deep learning."
"To enhance accessibility and user-friendliness, there is a need for improvements in the interface and usability of deep learning and large-scale learning languages."
"If they had a more structured training model it would be very helpful."
"From the point of view of the interface, they can do a little bit better."
"I'd like something that would make it easier to connect/parse websites, although I will fully admit that I'm not as proficient in KNIME as I would like to be, so it could be I'm just missing something."
"It could input more data acquisitions from other sources and it is difficult to combine with Python."
"It's pretty straightforward to understand. So, if you understand what the pipeline is, you can use the drag-and-drop functionality without much training. Doing the same thing in Python requires so much more training. That's why I use KNIME."
"KNIME's documentation is not strong."
"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."
"If they could include video tutorials, people would find that quite helpful."
"The price of this solution should be improved."
"RapidMiner can improve deep learning by enhancing the features."
"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."
"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."
