dbt Core v1.11 introduces user-defined functions (UDFs), allowing users to register custom functions within their dbt projects for better code reuse across their data stack. This release also emphasizes stricter authoring standards and includes various adapter-specific enhancements.

This article explains state-aware orchestration, a method that enables efficient data pipeline management by tracking the state of tables and their dependencies. It discusses how this approach can reduce unnecessary processing and costs, particularly in complex environments with multiple data sources and schedules.

The article discusses the misconception that dbt (data build tool) is purely declarative, highlighting its operational characteristics and the need for understanding its underlying mechanics. It emphasizes dbt's functionality beyond simple data transformation, showcasing its interactive nature in data workflows. The piece encourages readers to rethink their approach to using dbt effectively.

The dbt Fear Index has surged amid rumors of a potential Fivetran acquisition, leading to a significant increase in dbt forks as data engineers seek to maintain control over their projects. While many may never use these forks again, the situation highlights concerns over platform risks and the importance of dbt-core in modern data pipelines. Observers are curious about the implications of the acquisition rumors and the broader response within the data community.

The article discusses preparations for the upcoming dbt engine, highlighting new features and enhancements that users can expect. It emphasizes the importance of understanding these changes to optimize usage and leverage the new capabilities effectively. Additionally, it offers tips on transitioning smoothly to the updated engine.