data-governance

Explores the concept of semantic layers in business intelligence (BI) tools, which provide a governed and reusable data model for dashboards and reports. Covers topics like LookML, Power BI datasets, dbt Metrics, and how to build universal definitions, join logic, and shared dimensions/measures that can be leveraged across multiple BI platforms.

Best practices for implementing secure and governed data infrastructure, including role-based access controls, encryption, audit logging, and GDPR/CCPA compliance policies.

Paul Koullick argues that naming events well is a UX challenge. He lays out conventions for naming (verb-noun, title case, property bias), and introduces a workflow where every new event is reviewed for clarity and governance. Great for scaling teams.

João Lousada outlines how a data governance strategy prevents analytics drift. He emphasizes the role of casing rules, ownership tags, and source-of-truth documentation in keeping instrumentation aligned with product changes. Great for teams scaling analytics without chaos.