Introduction to dbt Cloud

Prerequisites:

• An understanding of data modeling and SQL
• Experience with SQL and command-line interface (CLI)
• Python programming experience

Audience

• Data Engineers
• Data Analysts
• Data Scientists

Overview:

dbt (data build tool) is an open-source command-line interface (CLI) tool used to manage and transform data in SQL-based data warehouses. dbt Cloud is the cloud-hosted version of the dbt tool that provides a user-friendly interface for managing and deploying dbt projects.

This instructor-led, live training (online or onsite) is aimed at beginner-level data engineers, analysts, and scientists who wish to understand how to use dbt Cloud to manage their data warehousing and transformation projects in the cloud.

By the end of this training, participants will be able to:

• Create and manage projects on dbt Cloud.
• Use the dbt Cloud interface to schedule and run data transformations.
• Collaborate on projects with team members.
• Deploy their dbt projects to production.
• Debug and troubleshoot dbt projects.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Course Outline:

Introduction

• dbt philosophy and principles / What is dbt?
• dbt vs traditional ETL
• Overview of dbt features and architecture
• Beyond dbt: What is dbt Cloud?

Understanding dbt Cloud

• The lifecycle of a dbt project in dbt Cloud
• How dbt Cloud fits in with data warehousing and transformation workflows

Getting Started with dbt Cloud

• Setting up the Development Environment on dbt Cloud
• Connecting dbt Cloud to your data warehouse
• Creating a dbt project in dbt Cloud
• Running dbt commands in dbt Cloud
• Collaborating with team members on a dbt project in dbt Cloud

Working with dbt Models

• Understanding dbt models
• Building a dbt model
• Transforming data using dbt
• Working with incremental models in dbt
• Implementing macros and custom functions in dbt

Managing dbt Projects in dbt Cloud

• Using the dbt Cloud interface to manage and deploy projects
• Creating schedules and triggering dbt jobs
• Creating and managing environments in dbt Cloud
• Deploying dbt projects to production
• Setting up notifications and alerts

Integrating dbt Cloud with Other Tools

• Using dbt Cloud with Git and version control
• Integrating dbt Cloud with other cloud-based data warehousing and transformation tools

Troubleshooting and Debugging

• How to debug and troubleshoot dbt projects in dbt Cloud
• Using logs to diagnose issues
• Best practices for maintaining dbt Cloud projects

Summary and Next Steps

Overview in Category:

This instructor-led, live training in <loc> (online or onsite) is aimed at beginner-level data engineers, analysts, and scientists who wish to understand how to use dbt Cloud to manage their data warehousing and transformation projects in the cloud.

By the end of this training, participants will be able to:

• Create and manage projects on dbt Cloud.
• Use the dbt Cloud interface to schedule and run data transformations.
• Collaborate on projects with team members.
• Deploy their dbt projects to production.
• Debug and troubleshoot dbt projects.