Badge 1: Data Warehousing Workshop
Start Here! Our Data Warehousing Workshop is designed for learners who are new to Snowflake, or new to databases in general. This workshop is highly interactive with reflection questions, hands on lab work and automated lab work checks! Fast-paced and informative, light in tone, scenario-driven and metaphor rich.
Hands-On Essentials Series
This course is the first in the Hands On Essentials Series. This series allows you to earn a Badge for display on LinkedIn and other social media. The Essentials Series uses active learning principles to give you a fast paced, hands on experience. Short videos, step-by-step labs, reflection questions, and challenge labs work together to build your knowledge and skills as you build a solution.
Prior Knowledge & Experience
As our flagship course, there are no prerequisites. You should know how to use a web browser but beyond that, you don't need to even need to know what a database is! It does NOT require prior experience with Snowflake.
We do our work alongside Tsai Yang, a data engineer who is reviewing Snowflake for her company's possible move to Snowflake. We also observe as Tsai introduces Snowflake and database concepts to her Uncle Yer, who has never used a database before but finds Snowflake clear and easy to learn.
Effort & Duration
Plan for 3 hours of effort a day for 3 days in a row. If you choose to complete the workshop in a single sitting, that's fine with us.
To complete the workshop you will run scripts that are autograded by DORA, our grading robot.
Don't sign up for a trial account until you are given step-by-step instructions within the course flow. Since this is the first course, we are more precise with the steps.
- Benefits of a Cloud-based Database
- Account Editions, Regions & Clouds
- Snowflake Identity, Access, Users, & Roles
- Databases, Ownership and Context
- Worksheets and Warehouses
- Loading Tables Using SQL Insert Statements
- File Formats, Stages, and Copy Into Loading
- Semi-Structured Data including XML and JSON
- Querying Nested Semi-Structured Data