EzzAbdelfattahAssociate Professor of Statistics at KAU
We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
"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."
"Personally for me, because I do a lot of development, I like that it is easy to test mathematical algorithms with several matrix calculations. It's perfect for that."
"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."
"To make use of the GPU, you have to have an Nvidia card. What I would want it to do is to run in Next Generation with Intel or AMD, and not just with Nvidia."
"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."
"We have a single user license. Support and add-ons are an extra fee."
Earn 20 points
IBM SPSS Statistics is ranked 5th in Data Science Platforms with 15 reviews while MathWorks Matlab is ranked 15th in Data Science Platforms with 1 review. IBM SPSS Statistics is rated 8.0, while MathWorks Matlab is rated 8.0. The top reviewer of IBM SPSS Statistics writes "Offers good Bayesian and descriptive statistics". On the other hand, the top reviewer of MathWorks Matlab writes "Test run my algorithms with ease before I develop the full software application". IBM SPSS Statistics is most compared with IBM SPSS Modeler, TIBCO Statistica, Weka, Alteryx and Microsoft Azure Machine Learning Studio, whereas MathWorks Matlab is most compared with Microsoft Azure Machine Learning Studio, Anaconda, Databricks, SAS Visual Analytics and Amazon SageMaker.
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