CF

The Data Bootcamp: Transform your Data using dbt™

4h 10m 51s
English
Paid

This course teaches you dbt™ from scratch. You follow a real project and see each step. You start with dbt Cloud. You connect it to Snowflake or another warehouse. You then build models, add sources, write tests, and use the docs.

What You Learn

You learn how dbt helps you shape and clean data. You write SQL models, and dbt runs them in the right order. You use SQL with Jinja to add logic. This gives you clear and repeatable steps in your project.

How dbt Works

You write code, then run it with the dbt run command. dbt builds only the models that need updates. This keeps your work fast. You test each model, update it, and run it again without long waits.

dbt also makes clean docs for your project. These docs help you track sources, models, and tests as your project grows.

Project You Build

You work with data from a sample company called GlobalMart. They sell home and office items. Their data team wants to test dbt for reports. They need clear tables for profit and other metrics.

You use dbt to shape their data and build these tables step by step. This shows you how a real team would use dbt in daily work.

About the Author: Udemy

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Udemy is the largest open marketplace for online courses on the internet. Founded in 2010 by Eren Bali, Oktay Caglar, and Gagan Biyani and headquartered in San Francisco, the company went public on the Nasdaq in 2021 under the ticker UDMY. The platform hosts well over two hundred thousand courses across software development, IT and cloud, data science, design, business, marketing, and creative skills, taught by tens of thousands of independent instructors. Roughly seventy million learners use it worldwide, and the corporate arm — Udemy Business — supplies a curated subset of that catalog to enterprise customers.

Because Udemy is a marketplace rather than a single editorial publisher, the catalog is uneven by design. The strongest material lives in the long-form, project-based courses authored by working engineers — full-stack JavaScript, React, Node.js, Python data science, AWS, Docker and Kubernetes, mobile development with Flutter and React Native, and cloud certification preparation. The CourseFlix listing under this source is the slice of that catalog that has been mirrored here for offline-friendly viewing, organized by topic and updated as new releases land. Pricing on Udemy itself swings dramatically with the site's near-permanent sales, which is why the platform is best treated as a deep reference catalog: pick instructors with strong reviews and a track record of updating their material rather than buying on the headline price alone.

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#1: Introduction to the Course
All Course Lessons (25)
#Lesson TitleDurationAccess
1
Introduction to the Course Demo
02:47
2
What is dbt?
04:08
3
ELT vs ETL - What is better?
04:46
4
How the Course is Structured
01:57
5
Reading the Project Brief
01:57
6
Setting up dbt Cloud
02:17
7
Setting up Snowflake Data Warehouse
17:53
8
Setting up Github
03:00
9
Connecting to the Database and Github
09:51
10
Initialising dbt Cloud
04:44
11
Taking a Tour of dbt Cloud
17:11
12
Developing Models in dbt
19:13
13
Understanding Modularity and REF Functions in dbt
31:26
14
Working with dbt_project.yml
06:52
15
Working with Sources in dbt
14:00
16
Introduction to Testing in dbt
03:05
17
How to Create Generic Tests in dbt
20:17
18
How to Create Singular Tests in dbt
10:32
19
How to Generate and work with dbt Documentation
16:36
20
How to use JINJA in dbt
13:02
21
How to Create Macros in dbt
13:16
22
How to use Packages in dbt
08:43
23
How to use Seeds (CSV files) in dbt
08:01
24
Deploying on dbt
14:33
25
A Quick Goodbye Note
00:44
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Frequently asked questions

What are the prerequisites for taking this course?
The course is designed to teach dbt from scratch, so no prior knowledge of dbt is required. However, a basic understanding of SQL will be beneficial since the course involves writing SQL models and using SQL with Jinja to add logic. Familiarity with data warehousing concepts and platforms like Snowflake might also be helpful, as you will connect dbt Cloud to a data warehouse during the course.
What will I build during the course?
During the course, you will work on a project for a sample company called GlobalMart, which sells home and office items. You will use dbt to transform their data and build tables for metrics such as profit. This project will guide you through shaping data into clear tables using real-world scenarios, demonstrating how a data team would use dbt for reporting purposes.
Who is the target audience for this course?
The course is aimed at individuals interested in learning how to transform data using dbt, such as data analysts, data engineers, and business intelligence professionals. It is suitable for those who are new to dbt and want to understand how it can be used in data transformation projects. People with a basic understanding of SQL and data warehousing concepts will find this course particularly beneficial.
What is the scope of this course compared to other dbt courses?
This course focuses on providing hands-on experience with dbt by following a real-world project from setup to deployment. It covers key concepts such as model development, testing, and documentation, using dbt Cloud as the platform. The course includes lessons on using Jinja for logic and building macros, which might not be covered in more introductory courses. It also teaches deployment practices and integration with platforms like Snowflake and Github.
What specific tools and platforms are covered in the course?
The course covers dbt Cloud, which is used to develop and deploy dbt projects. You will learn how to set up and connect dbt Cloud to a Snowflake data warehouse, although other warehouses can also be used. The course also includes instructions on setting up Github for version control, and it involves using SQL and Jinja for model logic and transformation processes.
What topics are not covered in this course?
The course does not cover advanced data engineering topics beyond dbt's capabilities, such as complex ETL pipelines or data visualization tools outside the context of dbt documentation. It also does not delve into advanced SQL optimization techniques or the broader architecture of data warehouses beyond their integration with dbt Cloud.
How can the skills learned in this course be applied to other careers or courses?
The skills learned in this course, such as data transformation using dbt, writing SQL models, and integrating with data warehouses, are applicable to roles in data analytics and data engineering. These skills are foundational for building efficient data workflows and can be valuable in any career involving data management and transformation. Additionally, the knowledge of dbt Cloud and platforms like Snowflake can be further expanded in more advanced data engineering and analytics courses.