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."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."
"Cloud-based process run helps in not keeping the systems on while processes are running."
"The most valuable feature is the set of visual data preparation tools."
"The solution is quite stable."
"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."
"If many teams are collaborating and sharing Jupyter notebooks, it's very useful."
"I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person."
"Data Science Studio's data science model is very useful."
"We have a local representative who specializes in SPSS. He will help us do the PoC."
"It's a very organized product. It's easy to use."
"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."
"Compared to other tools, the product works much easier to analyze data without coding."
"It is pretty scalable."
"IBM was chosen because of usability. It's point and click, whereas the other out-of-the box-solution, or open-source solutions, require full-on programming and a much higher skill level."
"It’s definitely scalable, it’s all on the same platform, it’s well integrated. I think the integration is important in terms of scalablility because essentially, having the entire suite helps a lot to scale it"
"So far, the stability has been rock solid."
"The ability to have charts right from the explorer would be an improvement."
"I think it would help if Data Science Studio added some more features and improved the data model."
"I find that it is a little slow during use. It takes more time than I would expect for operations to complete."
"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."
"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."
"Dataiku still needs some coding, and that could be a difference where business data scientists would go for DataRobot more than Dataiku."
"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."
"The product does not have a search function for tags."
"It would be good if IBM added help resources to the interface."
"Unstructured data is not appropriate for SPSS Modeler."
"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."
"Dimension reduction should be classified separately."
"Requires more development."
"If IBM could add some of the popular models into the SPSS for further analysis, like popular regression models, I think that would be a helpful improvement."
"Initial setup of the software was complex, because of our own problems within the government."
Dataiku is ranked 7th in Data Science Platforms with 7 reviews 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 "Gives different aspects of modeling approaches and good for multiple teams' collaboration". 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 Microsoft Power BI, KNIME, IBM SPSS Statistics, RapidMiner and SAP Predictive Analytics. See our Dataiku vs. IBM SPSS Modeler report.
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