Superpowering Agents with Apache Beam

Large language models and agentic systems are rapidly changing how exploratory data analytics is performed. Natural language interactions and assisted querying unlock quick prototyping for business experts without data science or programming backgrounds enabling them to get answers to business questions faster.

The limited context inherent in LLMs prevents direct analysis of large data volumes. Augmenting them with access to powerful tools, like databases, and query engines, and scalable data processing frameworks, overcomes this constraint.

This talk presents a use case of an agentic LLM that augments its capabilities by generating and running custom Apache Beam pipelines when the business insights require massive scale data processing.