Cloud Data Workflows for Scientists and Engineers: What You Should Know

Organizations are generating and collecting more data than ever before. Engineers and scientists need to unlock new discoveries and insights from this data. Accessing and managing such large amounts of data is expensive, complex and is beyond the expertise of most researchers. To overcome these barriers, organizations are moving data to the AWS^® cloud and using Databricks to speed up data analysis.

In this session, you will learn how to move data from an on-premises desktop environment to a research production environment on the cloud.

We will review how to:

• Bring data to AWS and use relevant analysis-optimized storage techniques
• Use the first and only lakehouse platform in the cloud. Databricks unifies all your data, analytics, and AI/ML motions on a simple, open, and collaborative cloud platform.
• Use MATLAB^® to connect to AWS and Databricks and harness cloud power in the code and toolboxes you trust, right from the desktop
• Share data, algorithms, and models in production at enterprise scale with MATLAB Production Server™ on AWS

Learn from AWS, Databricks, and MathWorks what lies ahead where desktop and local storage limitations no longer constrain innovation.