This three-day role-specific course covers key concepts, features, considerations, and Snowflake-recommended best practices through the lens of the data engineering workflow. It is intended for participants who will be accessing, developing, and querying datasets for analytic tasks and building data pipelines in Snowflake. This course consists of core data engineering concepts delivered through lectures, demos, labs, and discussions.

ACQUIRED SKILLS:

• Describe the data engineering workflow and how the Snowflake AI Data Cloud features support the various components of the workflow.
• Access Snowflake through the Snowsight UI and by using application methods.
• Load and unload data sets.
• Configure Snowflake features to cover a range of data ingestion and processing latencies.
• Develop applications for Snowflake, including comprehensive ANSI standard SQL support.
• Employ performance and cost optimization techniques.
• Use Snowflake’s capabilities to work eectively with structured, semi-structured, and unstructured data in Snowflake.
• Tune queries and improve performance using advanced techniques such as data clustering and materialized views.
• Employ Snowflake SQL extensibility features such as user-defined functions and stored procedures.