What you will learn
📥 Loading raw CSV data into Snowflake using Airbyte, configuring a file connector, and setting up a manual refresh for data loading.
🔍 How Airbyte loads data into a JSON variant column, making it more resilient to schema changes.
🛠 Creating initial YAML and SQL files using dbt coves by inspecting available tables in Snowflake.
🧩 Transforming raw data into structured models using the dbt_utils.surrogate_key macro to create a primary key.
🖥 Materializing data in Snowflake, running dbt models in VS Code, and previewing the transformed data.
🌐 Overview of Datacoves as a turnkey solution for modern data stack tools such as dbt, Airbyte, and Airflow, with flexibility for other tool integrations.
