Boost Data Science Productivity With Scalable AutoML and Code Automation
Data scientists are the innovation pioneers in an AI-driven world, where maximizing productivity isn’t just a goal—it’s a necessity to drive business value. Despite this pivotal role, data science teams encounter significant challenges like inefficient data preparation, manual machine learning (ML) processes, complex AI operationalization, and a daunting learning curve.
Join this live demo to see how Teradata VantageCloud and ClearScape Analytics™ can help you streamline data preparation and optimize ML workflows so you can deliver impactful insights to maintain your competitive edge.
During the demo, you’ll see how VantageCloud can help you:
- Perform complex data processing tasks directly within the database, bypassing common issues like data versioning, synchronization, and latency
- Maintain fresh datasets and improve reusability in a centralized, model-independent repository for model accuracy and timely decision making
- Retrieve past states of datasets, ensuring traceability and accountability in your projects
- Quickly identify optimal models using AutoML
- Automatically generate ClearScape Analytics code via a user-friendly interface
Presenter(s)
Tim Miller
Principal Software Architect, Product Management, Teradata
Tim Miller boasts a 30-year tenure at NCR Corporation and Teradata, playing pivotal roles in enterprise software development, including the creation of the first commercial in-database data mining system. His expertise in partner integration and data science consulting has led to his current position in Product Management managing the ClearScape Analytics suite of capabilities and as an instructor on Business Analytics at UCSD Halıcıoğlu Data Science Institute.
Denis Molin
Principal Data Scientist, Teradata
Dr. Denis Molin, an AI solutions expert at Teradata, specializes in deploying AI initiatives with Teradata Vantage and ClearScape Analytics. He leverages advanced SQL, Python, and open-source frameworks to transform complex data into actionable insights across industries like automotive, aerospace, and banking. Dr. Molin focuses on generative AI for enterprises and implements solutions such as Enterprise Feature Stores, effectively combining structured and unstructured data. With a Ph.D. in Physics, over 60 published papers, and more than 50 patents in both manufacturing and IT, his innovative work and practical demos offer valuable insights for data scientists seeking to advance their expertise.