Master Snowflake & dbt – from scratch to pro
InstructorDaniel WeigelInstruction includes real-world error correction, demonstrating how to resolve runtime issues during active lectures.
Editorial course preview
These 4 complementary views highlight concrete, legible examples from the course presentation.
This image shows a Snowflake SQL worksheet with a CREATE TASK script defining BIKE_TASK automation, followed by a confirmation that the task was successfully created.
This screen displays the dbt Lineage Graph tool, visualizing the dependencies and data flow between various models such as stg_btc_outputs and whale_alert within a Snowflake environment.
This screen capture shows a developer environment using Visual Studio Code to execute a dbt command, with the terminal confirming that the whale_alert model was created successfully.
The Snowflake interface displays a SQL query result table containing Bitcoin blockchain data columns such as BLOCK_NUMBER and BLOCK_TIMESTAMP.
The curriculum provides methods for connecting Snowflake to AWS, Azure, and Google Cloud Storage.
Covers essential production features including masking policies, role hierarchies, and automated Snowflake Tasks.
Small font sizes and high-resolution recordings can make code difficult to read on standard laptop screens.
