Expert Panel: Putting Machine Learning Models to Work in Your Organization
Webinar Speaker: James Kobielus, Senior Research Director, Data Management
Date: Wednesday, October 19, 2022
Time: 12:00 p.m. PT, 3:00 p.m. ET
Machine learning (ML) is the core of intelligent applications in the 21st-century economy. ML’s data-driven models power enterprises’ most mission-critical decision support, process automation, and customer engagement applications.
In this panel, TDWI senior research director James Kobielus will lead data industry experts in a discussion of how enterprises are putting ML models to work in their organizations. They will discuss such issues as:
- What investments should enterprises make to drive greater scale, speed, and automation in ML operationalization (MLOps) pipelines?
- What MLOps functions should be automated and which are best left partially or entirely reliant on the hands-on wizardry of professional data scientists?
- When should enterprises consider converging their MLOps siloes with their organizations’ data engineering infrastructures?
- How should enterprises evolve their MLOps practices and platforms to enable the next generation of ML-driven autonomous, robotics, embedded, and edge applications?
Joel T. McKelvey
Vice President of Product and Partner Marketing
Joel T. McKelvey is VP of product and partner marketing at Sisu, the AI and ML-powered Decision Intelligence Engine that analyzes data at machine scale. A former product manager at Google and leader of product marketing at Looker, he has an extensive background in data and analytics, including business intelligence, database and data storage, and analytics deployment models.
He holds master’s degrees from Columbia University and UC Berkeley as well as certificates from the California Institute of Technology, the Association of Strategic Alliance Professionals, Cisco, VMware, and others.
Date: October 19, 2022
Time: 9:00 am PT