Unlocking the Power of Generative AI for Structured Data

We are all familiar with using generative AI and large language models (LLMs) for processing and generating insights from unstructured text data. However, the capabilities of generative AI are evolving rapidly, extending into the realm of structured data. New tools and methodologies are now emerging that enable us to harness the power of AI to generate meaningful insights, recommendations, and even predictions from structured datasets, such as relational databases, spreadsheets, and CSV files. In this presentation, we will explore how these advancements are transforming the ways we interact with structured data, allowing AI to understand and derive context, identify patterns, and generate context-aware responses. Attendees will gain insights into practical applications, including how to integrate generative AI with their existing data infrastructure to unlock new levels of automation, decision-making, and efficiency in data analysis
 

James works at Microsoft as a big data and data warehousing solution architect where he has been for most of the last ten years. He is a thought leader in the use and application of Big Data and advanced analytics, including data architectures such as the modern data warehouse, data lakehouse, data fabric, and data mesh. He is a prior SQL Server MVP with nearly 40 years of IT experience. He is a popular blogger (JamesSerra.com) and speaker, having presented at dozens of major events. He is the author of the book “Deciphering Data Architectures: Choosing Between a Modern Data Warehouse, Data Fabric, Data Lakehouse, and Data Mesh”.