Transform Your Data Stack with dbt
10 Days
·Cohort-based Course
How to build a high-quality dbt project with proper documentation, tests, and reusable data models.
Transform Your Data Stack with dbt
10 Days
·Cohort-based Course
How to build a high-quality dbt project with proper documentation, tests, and reusable data models.
Course overview
Gain confidence in your ability to integrate dbt into your modern data stack.
Do you write a new query every time you need to answer a new business question? Do you find issues in your data when writing these queries but have no way to proactively find them? Do you find the same business logic coded over and over again with no lasting way to keep it consistent?
If your data stack...
- lacks standardization
- lacks organization
- lacks documentation and testing
- depends on a BI tool to store SQL and data models
- contains the same code in lots of different places
- gives minimal insight into data quality
...then this course is for you.
You will leave this course feeling confident that you can introduce (or refactor) dbt to create a data stack with minimal tech debt that will help you scale your team's data.
Requirements:
- proficiency in SQL
- proficiency in Git
- basic understanding of data transformation
- basic understanding of data warehouses
For those who want to leverage the powers of dbt.
01
You are a data analyst, data engineer, or other type of data professional who has heard about dbt but hasn't had the chance to learn it.
02
You are a beginner to intermediate-level data professional looking to add a new tool to your skillset.
03
You are ready to leverage your SQL knowledge and find a better way to transform and organize your data.
What you’ll get out of this course
Build a dbt project
- Discover how dbt can help solve your data problems
- Build a dbt project with an understanding of the different directories
- Write a style guide outlining best practices in your project
Document your data following best practices
- Identify the problems that dbt doc blocks can help solve and implement them in your project
- Dissect a model's lineage and understand how to build models with this in mind
- Simplify future debugging by implementing dbt exposures in your project
Define data quality tests using dbt packages
- Implement freshness tests and dbt generic tests to your data sources
- Integrate dbt packages into your project and use pre-built tests on your models
Write reusable data models and macros
- Identify differences between intermediate and core models
- Refactor code to make it more reusable
- Write a macro that can be used and referenced in multiple scenarios
Active learning and exercises with your data peers
- Build your project alongside others in the data community
- Connect with peers of all different experiences
This course includes
4 interactive live sessions
Lifetime access to course materials
17 in-depth lessons
Direct access to instructor
4 projects to apply learnings
Guided feedback & reflection
Private community of peers
Course certificate upon completion
Maven Satisfaction Guarantee
This course is backed by Maven’s guarantee. You can receive a full refund within 14 days after the course ends, provided you meet the completion criteria in our refund policy.
Transform Your Data Stack with dbt
Course syllabus
Week 1
May
14
Session 1- Elements of a dbt project
May
16
Session 2- Documentation
Building a dbt Project
Documentation Best Practices
Week 2
May
21
Session 3- Testing
May
23
Session 4- Reusability and Macros
Define data quality tests
Writing reusable data models and macros
Post-course
Putting everything you learned into action
Meet your instructor
Madison Schott
Senior Analytics Engineer and Technical Writer
Hi I'm Madison and I'll be your course instructor!
I was first introduced to dbt while working as a data engineer at Capital One. After first learning about dbt, I've been obsessed with the tool, as it inspired me to switch from data engineering to analytics engineering.
In my first few years as an analytics engineer, I built out an entire modern data stack at Winc from data warehouse to orchestration pipeline.
The biggest challenge here was refactoring SQL queries stored in a BI tool to be used in dbt. This caught me a lot about what not to do and how to build data models the right way.
Now I work at ConvertKit where I've helped build out our dbt project with best practices and reusable data models.
When I'm not solving data problems there, I'm most likely sharing what I've learned with the readers of my Learn Analytics Engineering newsletter.
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Transform Your Data Stack with dbt
Course schedule
3-5 hours per week
Mondays & Wednesdays
7:00pm - 8:30pm EST
Sessions will take place every Monday and Wednesday evening for 90 minutes, for 2 weeks.
May 13, 2024
The first session of the course.
- reading material
- live session w/ hands-on project
May 15, 2024
The second course session.
- reading material
- live session w/ hands-on project
May 20, 2024
The third course session.
- reading material
- live session w/ hands-on project
May 22, 2024
The last session of the course.
- reading material
- live session w/ hands-on project
Learning is better with cohorts
Active hands-on learning
This course builds on live workshops and hands-on projects
Interactive and project-based
You’ll be interacting with other learners through breakout rooms and project teams
Learn with a cohort of peers
Join a community of like-minded people who want to learn and grow alongside you
Frequently Asked Questions
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Transform Your Data Stack with dbt
What people are saying
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