We performed a comparison between IBM SPSS Statistics, KNIME, and SAS Enterprise Miner based on real PeerSpot user reviews.
Find out what your peers are saying about Knime, Weka, IBM and others in Data Mining.
"SPSS is quite robust and quicker in terms of providing you the output."
"in terms of the simplicity, I think the SPSS basic can handle it."
"The most valuable features mainly include factor analysis, correlation analysis, and geographic analysis."
"It has helped our analyst unit deliver work with more transparency and confidence, given that we can always view the dataset in totality, after each step of data transformation."
"It has the ability to easily change any variable in our research."
"The most valuable feature is its robust statistical analysis capabilities."
"Custom tables and macros: They allow us to create useful reports quickly for a broad audience."
"One feature I found very valuable was the analysis of variance (ANOVA)."
"It's a very powerful and simple tool to use."
"The most valuable is the ability to seamlessly connect operators without the need for extensive programming."
"Usability, and organising workflows in very neat manner. Controlling workflow through variables is something amazing."
"We are able to automate several functions which were done manually. I can integrate several data sets quickly and easily, to support analytics."
"The most valuable features of KNIME are its ability to convert your sub-workflow into a node. For example, the workflow has many individual native nodes that can be converted into a single node. This representation has simplified my workflow to a great extent. I can present my workflow in a very compact way."
"What I like the most is that it works almost out of the box with Random Forest and other Forest nodes."
"The visual workflow tools for custom and complex tasks always beat raw coding languages with the agility, speed to deliver, and ease of subsequent changes."
"The product is open-source and therefore free to use."
"The solution is able to handle quite large amounts of data beautifully."
"I found the ease of use of the solution the most valuable. Additionally, other valuable features include: the user interface, power to extract data, compatibility with other technologies (specifically with PS400), and automation of several tasks."
"The most valuable feature is the decision tree creation."
"The technical support is very good."
"he solution is scalable."
"The solution is very good for data mining or any mining issues."
"Good data management and analytics."
"I like the way the product visually shows the data pipeline."
"Technical support needs some improvement, as they do not respond as quickly as we would like."
"If there is any self-generation data collection plan (DCP), it would be helpful in gathering data. It would also be useful if there is a function to scale it up to, let's say, UiPath and have it consolidate and integrate into a UiPath solution."
"The design of the experience can be improved."
"I think the visualization and charting should be changed and made easier and more effective."
"One of the areas that should be similar to Minitabs is the use of blogs. The Minitabs blog helps users understand the tools and gives lots of practical examples. Following the SPSS manual is cumbersome. It's a good, exhaustive manual, but it's not practical to use. With Minitabs, you can go to the blogs and find specific articles written about various components and it's very helpful. Without blogs, we find SPSS more complicated."
"Better documentation on how to use macros."
"I feel that when it comes to conducting multiple analyses, there could be more detailed information provided. Currently, the software gives a summary and an overview, but it would be beneficial to have specific details for each product or variable."
"The statistics should be more self-explanatory with detailed automated reports."
"It could be easier to use."
"I would like to see better web scraping because every time I tried, it was not up to par, although you can use Python script."
"KNIME needs to provide more documentation and training materials, including webinars or online seminars."
"When deploying models on a regular system, it works fine. However, when accuracy is a priority, hyperparameter tuning is necessary. Currently, KNIME doesn't have the best tools for this which they could improve in this area."
"Though I can use KNIME in a 64-bit platform in the lab, it's missing some features. For example, from my laptop, I can use the image reader feature of KNIME. However, in the lab, the image reader node is missing."
"In the last update, KNIME started hiding a lot of the nodes. It doesn't mean hiding, but you need to know what you're looking for. Before that, you had just a tree that you could click, and you could get an overview of what kind of nodes do I have. Right now, it's like you need to know which node you need, and then you can start typing, but it's actually more difficult to find them."
"The documentation is lacking and it could be better."
"The ability to handle large amounts of data and performance in processing need to be improved."
"Technical support could be improved."
"Virtualization could be much better."
"The solution is very stable, but we do have some problems with discrepancies involving SAS not matching with the latest Java versions. It's not stable in cases where SAS tries to run on a different version because SAS doesn't connect with the latest Java update. Once a month we need to restart systems from scratch."
"The ease of use can be improved. When you are new it seems a bit complex."
"The solution needs an easier interface for the user. The user experience isn't so easy for our clients."
"The visualization of the models is not very attractive, so the graphics should be improved."
"The solution is much more complex than other options."
"The product must provide better integration with cloud-native technologies."
