Best practices for data modeling with SQL and dbt

The text discusses the challenges faced by analytics engineers in writing efficient SQL data models and how dbt, a data transformation tool, can help improve their functionality. It highlights best practices for writing good SQL code such as creating base models to reference raw data, using correct joins, minimizing duplicates at the source, using CTEs instead of subqueries, and creating dbt macros for repeatable SQL logic. The author emphasizes that following these practices from the beginning can prevent technical debt in the long run.