Transform Your Data Stack with dbt

New
·

10 Days

·

Cohort-based Course

How to build a high-quality dbt project with proper documentation, tests, and reusable data models.

ConvertKit
Capital One

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

12 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.

Course syllabus

Expand all modules
  • Post-Course

    Modules

    • Putting everything you learned into action

Meet your instructor

Madison Schott

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.

A pattern of wavy dots
Join an upcoming cohort

Transform Your Data Stack with dbt

Cohort 1

$650 USD

Dates

May 14—23, 2024

Payment Deadline

May 13, 2024
|

Bulk purchases

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

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

What happens if I can’t make a live session?
I work full-time, what is the expected time commitment?
A pattern of wavy dots
Join an upcoming cohort

Transform Your Data Stack with dbt

Cohort 1

$650 USD

Dates

May 14—23, 2024

Payment Deadline

May 13, 2024
|

Bulk purchases

$650 USD

10 Days

What people are saying

        What sets Madison apart is her approachable and relatable teaching style. Her explanations are always clear, concise, and to the point. Madison makes complex topics accessible even to those new to analytics engineering. Her ability to break down intricate concepts into digestible pieces is a gift.
Yordan Ivanov

Yordan Ivanov

Head of Data Engineering