From Chaos to Control: Automating BI Tools with Pydantic and Python

Maintaining Business Intelligent Tool (BI) governance, managing permissions, syncing documentation, and handling schema changes, can be chaotic. This talk explores how Python, Pydantic, and smart design patterns automate these tasks, ensuring seamless BI tool governance. Learn how to auto-sync table metadata, adjust queries on column renames, and enforce permissions effortlessly. With real-world examples, discover how to transform BI maintenance from a headache into a streamlined, automated process.

Basic Python

Managing Business Intelligence (BI) tools at scale can quickly become chaotic. Permissions must be enforced, documentation must stay up to date, and queries must be maintained, especially when schema changes occur. Without automation, these tasks become tedious, error-prone, and time-consuming.

In this talk, we’ll explore how to bring order to BI governance using Python, Pydantic, and effective design patterns. We’ll dive into three key automation strategies:

1. Automatic Permission System: Ensure users have access without manual intervention.
2. Documentation Synchronization: Keep table and column metadata up to date effortlessly.
3. Query Adjustments on Schema Changes: Prevent breaking queries by dynamically handling column renames.

Using real-world examples, we’ll explain how Python’s type validation and structured data models help enforce consistency, and how design patterns streamline these processes. Whether you're struggling with BI governance or looking for inspiration to optimize your data infrastructure, this session will provide actionable insights to help you shift from chaos to control.