dbt Learn

10 March, 2025Virtual

2 days
Virtual
Data Engineering
dbt
dbt labs

Welcome to the dbt Learn course! Are you starting out with dbt, or have some experience and want a formal overview of the ways of working including best practices? Or are you just eager to learn the go-to tool for modern data transformations.

With this open-source tool, you can transform data in warehouses simply with the power of SQL select statements. You will learn about modeling strategies, automated testing, and performance optimization. 

Book this training

Book now

Looking to upskill your team(s) or organization?

Rozaliia will gladly help you further with custom training solutions.

Rozaliia Khafizova
Data and AI Training Advisor

+31 6 11 58 19 37
Rozaliia.Khafizova@xebia.com
linkedin.com/in/rozaliya-khafizova

Get in touch

Duration

2 days

Time

09:00 – 13:00

Language

English

Lunch

Included

Certification

No

Level

Foundation

What will you learn?

After the training, you will be able to:

Write select statements in SQL to build robust models for your data

Design configurations to change the materialisations of each model

Combine Jinja and SQL to create scalable and advanced models

Take part in the dbt community through sharing knowledge

Program

By the end of this program, participants will have acquired a robust skill set in analytics engineering using dbt, enabling them to tackle real-world data challenges confidently.

  • The role of an analytics engineer
  • Fundamentals of a dbt project including best practices
  • Models to shape data from raw data to transformed data
  • Write, generate, and view documentation while you develop

This training is for you if:

You or your team is using or about to start using dbt

You want to learn the hottest tool for modeling data

You want ownership when it comes to working with your data

You want to automatically be added to gain the dbt Fundamentals badge

This training is not for you if:

You want to learn how to use Python to explore data (see Python for Data Analysis)

You have no experience working with SQL (see SQL for Data Analysis)

You do not work with data in a SQL data warehouse

You will not be working with dbt after the training

Why should I follow this training?

Earn the dbt fundamentals badge

Learn with hands-on real life examples – learn today apply tomorrow!

Become confident in the hottest data modeling tool

The dbt Fundamentals badge

After the training you will be invited to complete the dbt Fundamentals quiz, after which you will receive the dbt Fundamentals certification and badge!

What else
should I know?

After registering for this training, you will receive a confirmation email with practical information. A week before the training, the trainer will get in touch to ask you about any requirements you may have and any pre-course tasks you will need to do.

See you soon!

Course information

All learners have access to a data warehouse and dbt Cloud exclusively for the training

All literature and course materials are included in the price 

You need a laptop to take part in this training

You will be taken through demos and break out into groups to lock in the learning

Meet the trainers:

Lucy Sheppard 

Meet Lucy Sheppard, trainer at Xebia Data. Lucy is a data science trainer and teaches many Python courses as well as dbt Learn.

Guillermo Sanchez

Guillermo is a Principal Data Engineer at Xebia Data with extensive experience in the Data and AI Industry. His expertise is focused on developing and deploying data platforms and creating highly performant data pipelines. He has worked with many stacks and different cloud providers and enjoys designing simple but yet efficient architectures.

Pádraic Slattery

Padraic is a Technical Lead in the Analytics Engineering discipline with a passion for sharing his knowledge in dbt.

David Coba

David has a background in mathematical psychology, where he used statistics and data science to study human behavior. He also has a passion for software development and multiple years of experience teaching about technical topics.

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