We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
"The setup is straightforward. Deployment doesn't take more than 30 minutes."
"The solution is very good for data mining or any mining issues."
"he solution is scalable."
"Most of the features, especially on the data analysis tool pack, are really good. The way they do clustering and output is great. You can do fairly elaborate outputs. The results, the ensembles, all of these, are fantastic."
"The most valuable feature is the decision tree creation."
"The most valuable feature is that you can use multiple algorithms for creating models and then you can compare the results between them."
"Good data management and analytics."
"The solution is able to handle quite large amounts of data beautifully."
"The idea that you don't have to generate reports each day but they are sent automatically is great."
"We like the way we can drill down into each report to get back data on each project. From the portfolio level, I can see what is happening on it. That is a really important feature. I can look at indirect costs, for example, which are hitting each CIO portfolio. It's good to be able to see actual resources in terms of time as well as cost."
"The most valuable feature is the ease of setting up visualizations."
"The most valuable feature is the performance."
"The user interface of the solution needs improvement. It needs to be more visual."
"The solution is very stable, but we do have some problems with discrepancies involving SAS not matching with the latest Java versions. It's not stable in cases where SAS tries to run on a different version because SAS doesn't connect with the latest Java update. Once a month we need to restart systems from scratch."
"The solution needs an easier interface for the user. The user experience isn't so easy for our clients."
"Virtualization could be much better."
"The ease of use can be improved. When you are new it seems a bit complex."
"The visualization of the models is not very attractive, so the graphics should be improved."
"Technical support could be improved."
"While I don't personally need tutorials, I can't say that it wouldn't be helpful for others to have some to help them navigate and operate the system."
"Additional templates would help to get things moving more quickly in terms of getting the reports out."
"In terms of performance, I can see there are some issues when you are working with big data. When we are taking it from the Data Lake, we have a lot of issues."
"I would like the visualization for the map of countries to be more easily configurable."
"The scripting for customization could be improved."
"This solution is for large corporations because not everybody can afford it."
"The solution is expensive for an individual, but for an enterprise/institution (purchasing bulk licenses), it is not a high price for the use that will come from it."
Earn 20 points
TIBCO Spotfire Data Science is an enterprise big data analytics platform that can help your organization become a digital leader. The collaborative user-interface allows data scientists, data engineers, and business users to work together on data science projects. These cross-functional teams can build machine learning workflows in an intuitive web interface with a minimum of code, while still leveraging the power of big data platforms.
SAS Enterprise Miner is ranked 10th in Data Science Platforms with 10 reviews while TIBCO Data Science is ranked 18th in Data Science Platforms with 4 reviews. SAS Enterprise Miner is rated 7.6, while TIBCO Data Science is rated 7.6. The top reviewer of SAS Enterprise Miner writes "Good GUI, an easy initial setup, and very flexible". On the other hand, the top reviewer of TIBCO Data Science writes "A straightforward initial setup and good reporting but needs better documentation". SAS Enterprise Miner is most compared with IBM SPSS Modeler, Microsoft Azure Machine Learning Studio, SAS Analytics, RapidMiner and Amazon SageMaker, whereas TIBCO Data Science is most compared with TIBCO Statistica, KNIME, Dataiku Data Science Studio, IBM SPSS Statistics and MathWorks Matlab. See our SAS Enterprise Miner vs. TIBCO Data Science report.
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We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.