Predictive insights are the lifeblood of today’s business. Imagine that your product team is coming up with new features, your operations team is investigating supply chain issues, and your marketing team is developing 360-degree profiles of customers. Wondering what these three scenarios all have in common? For a modern business operating in today’s dynamic environment, all three are powered by predictive analytics.
Working behind the scenes, artificial intelligence and machine learning (AI/ML) enable high-value predictions that lay the groundwork for better decision-making. Advanced analytics, including generative AI, hold the power to sharpen your company’s competitive edge, drive operational efficiencies, and maximize growth.
With generative AI, data scientists can more easily make sense of ever-growing datasets. They can automate tedious tasks like filtering and parsing huge volumes of data so they can draw out meaningful information.
Join us to learn how leaders are overcoming the common pitfalls around AI workflows, how Teradata and Amazon Web Services (AWS) are penetrating barriers to predictive analytics, and how data scientists can scale analytics leveraging an integrated AI toolset.
Bogdan Vrusias leads the AWS pan-EMEA AI/ML Specialist Solutions Architecture team. He has over 25 years of professional and academic experience in researching, designing, and implementing complex AI/ML solutions. For the last five years at AWS, Bogdan has been supporting customers in building state-of-the-art solutions spanning from generative AI to traditional machine learning.
Chris Hillman is Senior Director of Data Science in the International region and has been responsible for developing and articulating Teradata’s AI and generative AI analytics strategy. Chris previously led the International Data Science Practice and has worked on a large number of AI projects focusing on the generation of measurable ROI from analytics in production at scale using Teradata, open-source, and other vendor technologies.