EzzAbdelfattahAssociate Professor of Statistics at KAU
Hemant AddalSenior Vice President at a financial services firm
We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
"Very good data aggregation."
"It is a great product for running statistical analysis."
"Automation is great and this product is very organized."
"You take two quarters and compare them and this tool is ideal because it gives you a lot of visibility on the before and after."
"The supervised models are valuable. It is also very organized and easy to use."
"This open-source product can compete with category leaders in ELT software."
"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."
"This solution is easy to use and especially good at data preparation and wrapping."
"It's a coding-less opportunity to use AI. This is the major value for me."
"This solution is easy to use and it can be used to create any kind of model."
"All of the features related to the ETL are fantastic. That includes the connectors to other programs, databases, and the meta node function."
"What I like the most is that it works almost out of the box with Random Forest and other Forest nodes."
"It is very fast to develop solutions."
"Requires more development."
"It would be good if IBM added help resources to the interface."
"Dimension reduction should be classified separately."
"When you are not using the product, such as during the pandemic where we had worldwide lockdowns, you still have to pay for the licensing."
"Time Series or forecasting needs to be easier. It is a very important feature, and it should be made easier and more automated to use. For instance, for logistic regression, binary or multinomial is used automatically based on the type of the target variable. I wish they can make Time Series easier to use in a similar way."
"The ability to handle large amounts of data and performance in processing need to be improved."
"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."
"It needs more examples, use cases, and MOOC to learn, especially with respect to the algorithms and how to practically create a flow from end-to-end."
"There should be better documentation and the steps should be easier."
"KNIME needs to provide more documentation and training materials, including webinars or online seminars."
"The predefined workflows could use a bit of improvement."
"The documentation is lacking and it could be better."
"There are a lot of tools in the product and it would help if they were grouped into classes where you can select a function, rather than a specific tool."
"This tool, being an IBM product, is pretty expensive."
"Its price is okay for a company, but for personal use, it is considered somewhat expensive."
"KNIME is free as a stand-alone desktop-based platform but if you want to get a KNIME server then you can find the cost on their website."
"The price of KNIME is quite reasonable and the designer tool can be used free of charge."
"It's an open-source solution."
"The price for Knime is okay."
"At this time, I am using the free version of Knime."
"This is an open-source solution that is free to use."
"There is a Community Edition and paid versions available."
IBM SPSS Modeler is an extensive predictive analytics platform that is designed to bring predictive intelligence to decisions made by individuals, groups, systems and the enterprise. By providing a range of advanced algorithms and techniques that include text analytics, entity analytics, decision management and optimization, SPSS Modeler can help you consistently make the right decisions from the desktop or within operational systems.
IBM SPSS Modeler is ranked 3rd in Data Mining with 5 reviews while KNIME is ranked 1st in Data Mining with 14 reviews. IBM SPSS Modeler is rated 8.4, while KNIME is rated 8.4. The top reviewer of IBM SPSS Modeler writes "User-friendly, and it gives you a lot of visibility through features like comparing fiscal quarters". On the other hand, the top reviewer of KNIME writes "Has good machine learning and big data connectivity but the scheduler needs improvement ". IBM SPSS Modeler is most compared with IBM SPSS Statistics, IBM Watson Studio, Alteryx, Microsoft BI and Microsoft Azure Machine Learning Studio, whereas KNIME is most compared with Alteryx, RapidMiner, Databricks, Weka and Microsoft BI. See our IBM SPSS Modeler vs. KNIME report.
We monitor all Data Mining 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.