SAS Enterprise Miner and Microsoft Azure Machine Learning Studio compete in the data analytics space. Microsoft Azure often has an upper hand due to its flexible deployment options and comprehensive AI capabilities.
Features: SAS Enterprise Miner offers advanced predictive modeling, text mining, and statistical processing. It excels in data management and analytics, decision tree creation, and cluster analysis. Microsoft Azure Machine Learning Studio features seamless cloud integration, an extensive algorithm library, and rapid model deployment capabilities. It integrates well with other Microsoft services and offers a user-friendly drag-and-drop interface.
Room for Improvement: SAS Enterprise Miner could enhance its cloud integration and simplify its complex interface. Its flexibility could be improved for handling diverse data sources and providing more streamlined deployment options. Microsoft Azure Machine Learning Studio may improve its transformation capabilities, enhance automation for distributed computing, and refine its data cleansing tools to accelerate workflows and reduce manual intervention.
Ease of Deployment and Customer Service: SAS Enterprise Miner requires significant IT expertise for deployment, which can be complex. Its customer support is robust but may not match Microsoft's extensive support framework. Microsoft Azure benefits from a cloud-based setup, simplifying deployment and scalability. Its customer service is perceived as responsive and accessible due to Microsoft's extensive support network.
Pricing and ROI: SAS Enterprise Miner involves higher initial setup costs and ongoing licensing fees, leading to a longer ROI period. In contrast, Microsoft Azure Machine Learning Studio provides flexible pricing models aligned with cloud consumption, offering faster ROI through lower initial investments and operational flexibility.
Azure Machine Learning is a cloud predictive analytics service that makes it possible to quickly create and deploy predictive models as analytics solutions.
It has everything you need to create complete predictive analytics solutions in the cloud, from a large algorithm library, to a studio for building models, to an easy way to deploy your model as a web service. Quickly create, test, operationalize, and manage predictive models.
Microsoft Azure Machine Learning Will Help You:
With Microsoft Azure Machine Learning You Can:
Microsoft Azure Machine Learning Features:
Microsoft Azure Machine Learning Benefits:
Reviews from Real Users:
"The ability to do the templating and be able to transfer it so that I can easily do multiple types of models and data mining is a valuable aspect of this solution. You only have to set up the flows, the templates, and the data once and then you can make modifications and test different segmentations throughout.” - Channing S.l, Owner at Channing Stowell Associates
"The most valuable feature is the knowledge bank, which allows us to ask questions and the AI will automatically pull the pre-prescribed responses.” - Chris P., Tech Lead at a tech services company
"The UI is very user-friendly and the AI is easy to use.” - Mikayil B., CRM Consultant at a computer software company
"The solution is very fast and simple for a data science solution.” - Omar A., Big Data & Cloud Manager at a tech services company
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.