We performed a comparison between Dataiku and IBM SPSS Statistics 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."Data Science Studio's data science model is very useful."
"The solution is quite stable."
"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 most valuable feature is the set of visual data preparation tools."
"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."
"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."
"The features that I have found most valuable are the Bayesian statistics and descriptive statistics."
"Some of the most valuable features that we are using with some business models are machine learning algorithms, statistical models given to us by the business, and getting data from the database or text files."
"One feature I found very valuable was the analysis of variance (ANOVA)."
"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."
"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."
"The most valuable feature is the user interface because you don't need to write code."
"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."
"You can quickly build models because it does the work for you."
"I think it would help if Data Science Studio added some more features and improved the data model."
"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."
"Server up-time needs to be improved. Also, query engines like Spark and Hive need to be more stable."
"Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days)."
"I find that it is a little slow during use. It takes more time than I would expect for operations to complete."
"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."
"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."
"Improvements are needed in the user interface, particularly in terms of user-friendliness."
"Better documentation on how to use macros."
"I know that SPSS is a statistical tool but it should also include a little bit of analytical behavior. You can call it augmented analysis or predictive analysis. The bottom line is it should have more graphical and analytical capabilities."
"The statistics should be more self-explanatory with detailed automated reports."
"It could allow adding color to data models to make them easier to interpret."
"Most of the package will give you the fixed value, or the p-value, without an explanation as to whether it it significant or not. Some beginners might need not just the results, but also some explanation for them."
"SPSS is a tool that's been around since the late 60s, and it's the universal worldwide standard for quantitative social science data analysis. That said, it does seem a bit strange to me that the graphical output functions are so clunky after all these years. The output of charts and graphs that SPSS produces is hideous."
"It would be helpful if there was better documentation on how to properly use the solution. A beginner's guide on how to use the various programming functions within the product would be so useful to a lot of people. I found that everything was very confusing at first. Having clear documentation would help alleviate that."
Dataiku is ranked 11th in Data Science Platforms while IBM SPSS Statistics is ranked 7th in Data Science Platforms with 36 reviews. Dataiku is rated 8.2, while IBM SPSS Statistics 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 Statistics writes "Enhancing survey analysis that provides valued insightfulness". Dataiku is most compared with Databricks, KNIME, Alteryx, RapidMiner and Starburst Galaxy, whereas IBM SPSS Statistics is most compared with Alteryx, TIBCO Statistica, Microsoft Azure Machine Learning Studio, Weka and Anaconda. See our Dataiku vs. IBM SPSS Statistics report.
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