Abstract: Without doubt, putting analytics into action is one of the biggest challenges across industries. To generate business value from analytics investments, organizations need to adopt ModelOps practices to streamline the way they validate and deploy analytical models. However, implementing a ModelOps approach is not a simple task as it involves many technical and non-technical (i.e. cultural, organizational) aspects.
In this session, we will discuss some of the technical key principles of ModelOps and we will demonstrate a pipeline approach to quickly move from development to test and production using a mix of Python, SAS® Viya and other CI/CD tools.
Bio: Matteo is a data scientist at SAS. He supports global initiatives and projects that involves advanced analytics and artificial intelligence technologies. He is passionate about helping companies transforming their business processes with analytics.
Matteo has a MSc in Management Engineering from Politecnico di Milano, with a specialization in Industrial Management