Thijs Bressers
Building Python-first data systems at the intersection of modern data stacks and corporate intelligence, with a focus on integration, modelling, and reliability.
Session
Dashboards tell you what happened. They rarely tell you when it matters.
In this talk, we present a Python-first approach to building active KPI systems on top of the modern data stack. Using a semantic model to define metrics, dimensions, and business logic, we move beyond static dashboards toward event-driven data workflows.
We’ll show how to define KPIs as code using typed schemas, compute them using DuckDB, and attach intelligent alerting that triggers when meaningful changes occur. Not just threshold breaches. Instead of brittle “if > X then alert” logic, we introduce context-aware rules, anomaly detection, and dependency aware KPI evaluation.
We’ll also cover a lightweight Python-based alerting framework that integrates with common tools (Slack, email, APIs), enabling self-service data monitoring.
Attendees will learn how to turn passive dashboards into operational data system. And yes, while it could be enhanced with, in its core this works entirely without LLMs.
Example code and a minimal alerting framework will be shared.