We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
Earn 20 points
IBM Watson Studio provides tools for data scientists, application developers and subject matter experts to collaboratively and easily work with data to build and train models at scale. It gives you the flexibility to build models where your data resides and deploy anywhere in a hybrid environment so you can operationalize data science faster.
SAS Visual Data Mining and Machine Learning combines data wrangling, data exploration, visualization, feature engineering, and modern statistical, data mining and machine learning techniques all in a single, scalable in-memory processing environment. This provides faster, more accurate answers to complex business problems, increased deployment flexibility and one easy-to-administer and fluid IT environment.
IBM Watson Studio is ranked 12th in Data Science Platforms with 6 reviews while SAS Visual Data Mining and Machine Learning is ranked 25th in Data Science Platforms. IBM Watson Studio is rated 8.2, while SAS Visual Data Mining and Machine Learning is rated 0.0. The top reviewer of IBM Watson Studio writes "Machine learning that can be applicable for other data sets without having to carry out the process all over again". On the other hand, IBM Watson Studio is most compared with Microsoft Azure Machine Learning Studio, IBM SPSS Modeler, Google Cloud Datalab, Amazon SageMaker and Databricks, whereas SAS Visual Data Mining and Machine Learning is most compared with SAS Visual Analytics, SAS Enterprise Miner, Microsoft Azure Machine Learning Studio, KNIME and Alteryx.
See our list of best Data Science Platforms vendors.
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.