Marinela Profi is responsible for the integration of SAS Viya with open source technology and data science practice. Previously, Profi worked as an analytic and AI consultant. Over the past 5 years, Profi honed her skills mining data, developing models and technical/business solutions, including deploying AI at scale. She holds a Master’s in Statistics and a Master in Business Administration degree.
[Editor's note: this post was co-authored by Marinela Profi and Wilbram Hazejager] Data science teams are multidisciplinary, each with different skills and technologies of choice. Some of them use SAS, others may have analytical assets already built in Python or R. Let's just say each team is unique. As part
Turn analytical models into business value and smarter decisions with this special collection of papers about SAS Model Management. Without a structured and standardized process to integrate and coordinate all the different pieces of the model life cycle, a business can experience increased costs and missed opportunities. SAS Model Management solutions enable organizations to register, test, deploy, monitor, and retrain analytical models, leveraging any available technology – including open-source models in Python, R, and TensorFlow –into a competitive advantage.
