DBT For Data Engineers

Learn Analytics Engineering Using Open Source DBT

In this course we will go from beginner to implementing advanced data pipelines with clean, maintainable models using DBT.

Introduction To DBT

Introducing DBT and the value it brings to data teams.

View
Hands-On Lab

Creating A DBT Project

Using the DBT Command Line Interface to create and configure our first DBT project.

View
Hands-On Lab

Configuring DBT Profiles

The DBT profile system and best practices for managing profiles for maintainable code.

View
Hands-On Lab

Executing Your First Transformations

Implementing and running our first transformations using DBT models that build both tables and views.

View
Hands-On Lab

DBT Views and Tables

Using DBT to materialise to tables and views, and the associated incremental and ephemeral options.

View
Hands-On Lab

Seed Data

Using DBTs seed data feature to reliably populate our database with static data for use as part of DBT transformations.

View

Testing With DBT

Using the testing features of DBT to validate data transformations and pipelines.

View
Hands-On Lab

Incremental Views

Learning about DBTs incremental updates and incremental views.

View
Hands-On Lab

Ethemeral Views

Using DBTs ethemeral view feature to improve your pipeline readability.

View
Hands-On Lab

Sources and Exposures

Using DBTs source and exposure features to capture better metadata regarding your pipelines.

View

Documenting Your Models

DBTs features for automatically generating documentation.

View

© 2022 Timeflow Academy.