We performed a comparison between Dataiku and IBM SPSS Modeler based on real PeerSpot user reviews.
Find out in this report how the two Data Science Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The most valuable feature of this solution is that it is one tool that can do everything, and you have the ability to very easily push your design to prediction."
"The most valuable feature is the set of visual data preparation tools."
"Cloud-based process run helps in not keeping the systems on while processes are running."
"I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person."
"The solution is quite stable."
"Data Science Studio's data science model is very useful."
"Extremely easy to use with its GUI-based functionality and large compatibility with various data sources. Also, maintenance processes are much more automated than ever, with fewer errors."
"It handles large data better than the previous system that we were using, which was basically Excel and Access. We serve upwards of 300,000 parts over a 150 regions and we need to crunch a lot of numbers."
"It works fine. I have not had any stability issues; it is always up."
"Automated modelling, classification, or clustering are very useful."
"Our go live process has been slightly enhanced compared to the previous programmatic process. There is now a faster time to production from the business end."
"I think it is the point and drag features that are the most valuable. You can simply click at the windows, and then pull up the functions."
"It will scale up to anything we need."
"We are using it either for workforce deployment or to improve our operations."
"I think the code modeling features are the most valuable and without the need to write a code back with many different possibilities to choose from. And the second one is linked to the activity of the data preparation."
"There were stability issues: 1) SQL operations, such as partitioning, had bugs and showed wrong results. 2) Due to server downtime, scheduled processes used to fail. 3) Access to project folders was compromised (privacy issue) with wrong people getting access to confidential project folders."
"The interface for the web app can be a bit difficult. It needs to have better capabilities, at least for developers who like to code. This is due to the fact that everything is enabled in a single window with different tabs. For them to actually develop and do the concurrent testing that needs to be done, it takes a bit of time. That is one improvement that I would like to see - from a web app developer perspective."
"I think it would help if Data Science Studio added some more features and improved the data model."
"The ability to have charts right from the explorer would be an improvement."
"In the next release of this solution, I would like to see deep learning better integrated into the tool and not simply an extension or plugin."
"Server up-time needs to be improved. Also, query engines like Spark and Hive need to be more stable."
"I find that it is a little slow during use. It takes more time than I would expect for operations to complete."
"Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days)."
"Initial setup of the software was complex, because of our own problems within the government."
"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."
"I can say the solution is outdated."
"Formula writing is not straightforward for an Excel user. Totally new set of functions, which takes time to learn and teach."
"The platform that you can deploy it on needs improvement because I think it is Windows only. I do not think it can run off a Red Hat, like the server products. I am pretty sure it is Windows and AIX only."
"Regarding visual modeling, it is not the biggest strength of the product, although from what I hear in the latest release it's going to be a lot stronger. That, to me, has always been the biggest flaw in using this. It's very difficult to get good visualization."
"Dimension reduction should be classified separately."
"C&DS will not meet our scalability needs."
Dataiku is ranked 11th in Data Science Platforms while IBM SPSS Modeler is ranked 12th in Data Science Platforms with 38 reviews. Dataiku is rated 8.2, while IBM SPSS Modeler is rated 8.0. The top reviewer of Dataiku writes "The model is very useful". On the other hand, the top reviewer of IBM SPSS Modeler writes "Easy to use, quick to learn, and offers many ways to analyze data". Dataiku is most compared with Databricks, KNIME, Alteryx, RapidMiner and IBM Watson Studio, whereas IBM SPSS Modeler is most compared with KNIME, Microsoft Power BI, RapidMiner, IBM SPSS Statistics and IBM Watson Studio. See our Dataiku vs. IBM SPSS Modeler report.
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