Configuring dbt Model Access using Grants: A Practical Example
Learn how to configure dbt grants so data engineers can query all models, data analysts can query Gold models, and data scientists can query one specific model.
Get prepared for the dbt Analytics Engineering Certification exam and become a certified dbt Analytics Engineer. Learn key concepts, best practices, and hands-on techniques to master dbt, Data Modeling, and Analytics. Start your journey to certification today!
Learn how to configure dbt grants so data engineers can query all models, data analysts can query Gold models, and data scientists can query one specific model.
Learn how dbt state works with a practical state:modified example using a production manifest.json and a changed dim_student model.
Learn how dbt clone works with a practical dim_student example using production state artifacts and a development target schema.
Learn how to use dbt snapshots with a practical student example, the timestamp strategy, updated_at, and historical records.
Learn how dbt --defer works with a practical dim_student example using --state, a production manifest, and upstream model references.
Learn dbt incremental models with a practical enrollment_cleaned example using materialized incremental, unique_key, is_incremental(), updated_at, and data tests.
Learn how to build business-ready fact and dimension tables in dbt using a simple Gold layer example with dim_course, dim_student, and fact_enrollment.
Learn what dbt snapshots are, why they matter, and how to track historical changes in your data warehouse with a beginner-friendly customer status example.
Learn what dbt exposures are, why they matter, and how to connect dbt models to dashboards, reports, notebooks, and machine learning workflows.