Giuseppe-NaldiPrincipal Full Stack Data Scientist at ICTeam
EzzAbdelfattahAssociate Professor of Statistics at KAU
We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
"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."
"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."
"Most of the product features are good but I particularly like the linear regression analysis."
"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."
"The best part is that they have an algorithm handbook, so you can open it up and understand how it works, and if it is useful, this is very important."
"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."
"They have many existing algorithms that we can use and use effectively to analyze and understand how to put our data to work to improve what we do."
"It has the ability to easily change any variable in our research."
"The most valuable feature is the user interface because you don't need to write code."
"In terms of the features I've found most valuable, I'd say the duration, the correlation, and of course the nonparametric statistics. I use it for reliability and survival analysis, time series, regression models in different solutions, and different types of solutions."
"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."
"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."
"I think the visualization and charting should be changed and made easier and more effective."
"Technical support needs some improvement, as they do not respond as quickly as we would like."
"The statistics should be more self-explanatory with detailed automated reports."
"Each algorithm could be more adaptable to some industry-specific areas, or, in some cases, adapted for maintenance."
"The product should provide more ways to import data and export results that are user-friendly for high-level executives."
"The design of the experience can be improved."
"This solution is not suitable for use with Big Data."
"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."
"The annual licensing fees are approximately €20 ($22 USD) per key for the basic version and €40 ($44 USD) per key for the version with everything."
"We think that IBM SPSS is expensive for this function."
"The price of this solution is a little bit high, which was a problem for my company."
"The pricing of the modeler is high and can reduce the utility of the product for those who can not afford to adopt it."
Dataiku DSS is the collaborative data science software platform for teams of data scientists, data analysts, and engineers to explore, prototype, build, and deliver their own data products more efficiently.
Dataiku Data Science Studio is ranked 11th in Data Science Platforms with 4 reviews while IBM SPSS Statistics is ranked 5th in Data Science Platforms with 15 reviews. Dataiku Data Science Studio is rated 8.0, while IBM SPSS Statistics is rated 8.0. The top reviewer of Dataiku Data Science Studio writes "User interface is colorful, beautiful, and well-designed but sometimes the solution can be slow". On the other hand, the top reviewer of IBM SPSS Statistics writes "Offers good Bayesian and descriptive statistics". Dataiku Data Science Studio is most compared with Alteryx, Databricks, KNIME, Microsoft Azure Machine Learning Studio and TIBCO Data Science, whereas IBM SPSS Statistics is most compared with IBM SPSS Modeler, MathWorks Matlab, TIBCO Statistica, Weka and RapidMiner. See our Dataiku Data Science Studio vs. IBM SPSS Statistics report.
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