Manual analysis of thousands of daily database alerts is impossible—but AI changes everything. This talk demonstrates using modern AI tools to analyze internal alert databases and uncover critical patterns in ClickHouse® database deployments. 

Data lakes on open table formats like Iceberg are a popular way to manage large datasets for analytics, data science, and AI. This talk explains how data lakes work and how to adapt open source analytic stacks to use them.
First, we’ll tour projects like Arrow, Iceberg, and Unity Catalog that make data lakes possible. Next, we’ll see how analytic engines like DuckDB, ClickHouse, and Spark are adapting. Finally, we’ll survey a few projects that enable applications written in Python, Golang, or Rust to deliver fast query.
You’ll have to build the app yourself but this talk will show you a path to use data lakes and open source successfully.