Saurabh Bhutyani

Data-driven organizations need to ensure that the right data is accessed by the right user for the right purpose—in accordance with the organization’s security regulations—without relying on individual credentials.

Generative AI applications are powered by foundation models or large language models that are trained on large volumes of data. They have several emerging data patterns including in-context learning, model fine-tuning, and build your own model.

In this chalk talk, learn how to design and implement modern analytics architectures, including data mesh, fabric, and virtualization, that break down data silos and drive analytics agility using Amazon Athena’s data source connectors and open data formats.

Organizations want analytics solutions that are easy to set up and maintain while delivering the powerful analytics required to succeed with a modern data strategy. This chalk talk covers how you can use Amazon Athena to build powerful capabilities, like real-time fraud detection, and enable data scientists to build and train ML models across all of your data.