Top 8 Data Science Platforms
DatabricksAlteryxMicrosoft Azure Machine Learning StudioKNIMEIBM SPSS StatisticsRapidMinerIBM SPSS ModelerDataiku Data Science Studio
The most valuable feature of Databricks is the integration with Microsoft Azure.
This solution offers a lake house data concept that we have found exciting. We are able to have a large amount of data in a data lake and can manage all relational activities.
Alteryx effectively visualizes the flow of data and what happens at each stage. I also like that it's a no-code solution. I also like that you can troubleshoot certain parts of the workflow by putting them in a sandbox.
It's easy to deploy.
Auto email and studio are great features.
We have found KNIME valuable when it comes to its visualization.
Overall KNIME serves its purpose and does a good job.
The most valuable feature of IBM SPSS Statistics is all the functionality it provides. Additionally, it is simple to do the five-way analysis that you can into multidimensional setup space. It's the multidimensional space facility that is most useful.
We value the collaboration and governance features because it's a comprehensive platform that covers everything from data extraction to modeling operations in the ML language. RapidMiner is competitive in the ML space.
The most valuable features of the IBM SPSS Modeler are visual programming, you don't have to write any code, and it is easy to use. 90 to 95 percent of the use cases, you don't have to fine-tune anything. If you want to do something deeper, for example, create a better neural network, then you have to go into the features and try to fine-tune them. However, the default selection which is made by the tool, it's very practical and works well.
Data Science Studio's data science model is very useful.
The solution is quite stable.