Course Overview
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.
What are the skills covered
- 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 effectively 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.
Who should attend this course
- Data Analysts
- Data Engineers
- Data Scientists
- Database Architects
- Database Administrators
- Data Application Developers
Course Curriculum
Course Modules
Exam & Certification
The SnowPro® Advanced: Data Engineer Certification DEA-C02.
SNOWPRO ADVANCED: DATA ENGINEER OVERVIEW
This certification will test the ability to:
- Source data from Data Lakes, APIs, and on-premises
- Transform, replicate, and share data across cloud platforms
- Design end-to-end near real-time streams
- Design scalable compute solutions for Data Engineer workloads
- Evaluate performance metrics
