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Become a dbt professional from scratch with this single course, solving a real-world problem step by step! We cover both theory and hands-on practice! Delivered by an instructor with 20+ years of Data Engineering experience   ✨✨ June 2023 update to the most recent version of dbt, 1.5! ✨✨


"Excellent course! Edit: I managed to pass the dbt certification exam. I couldn't have done it without your help! Again, it's an awesome course!"

⭐️⭐️⭐️⭐️⭐️ Agnit Chatterjee

"Fantastic course. Well-chosen examples perfectly illustrate the many features that are covered. The pacing is spot on and it is easy to replicate the examples."

⭐️⭐️⭐️⭐️⭐️ Ricky McMaster


"I love how you're explaining everything at just the right level!"

⭐️⭐️⭐️⭐️⭐️ William Jahn


Greetings to the MOST COMPLETE, CONTINUOUSLY UPDATED independent dbt (Data Build Tool) software course in the world - as of 2023! This course is the TOP RATED and the BESTSELLER dbt course on Udemy!


Thank you for joining us for The Complete dbt (Data Build Tool) Bootcamp: Zero to Hero - we are super excited to have you in the course!

The structure of the course is designed to have a top-down approach. It starts with the Analytics Engineering Theory - all you need to know is to put dbt (Data Build Tool) in context and to have an understanding of how it fits into the modern data stack. We start with the big picture; then, we go deeper and deeper. Once you learn about the pieces, we are going to shift to the technicalities - a practical section -, which will focus on putting together the dbt “puzzle”. The practical section will cover each and every single dbt feature present today through the construction of a complete, real-world project; Airbnb. This presents an opportunity for us to show you which features should be used at what stage in a given project, and you will see how dbt is used in the industry.


RECENT UPDATES:

Course Updated to dbt 1.5 - May 2023

Fully pastable course materials on GitHub and lecture notes added about common pitfalls in dbt setup - Jan 2023

Added Great Expectations and test debugging sections - Sep 2022

Radically simplified Windows installation instructions (no WSL needed anymore)  - Sep 2022

The course is tested in dbt cloud - Aug 2022

Added Modern Data Stack overview - Jun 2022


THEORETICAL SECTION:

Among several other topics, the theoretical section puts special emphasis on transferring knowledge in the following areas;

  • Data-Maturity Model

  • Well-functioning Data Architectures

  • Data Warehouses, Data Lakes, and Data Lakehouses

  • ETL and ELT procedures and Data Transformations

  • Fundamentals of dbt (Data Build Tool)

  • Analytics Engineering

  • Modern Data Stack

  • Slowly Changing Dimensions

  • CTEs

Once we understood the theoretical layer and how dbt fits into the picture, we are going to start building out a dbt project from scratch, just as you would do this in the real world.


PRACTICAL SECTION:

The practical section will go through a real-world Airbnb project where you will master the ins and outs of dbt! We put special focus on getting everyone up and ready before the technical deep dive, hence we will start off by setting up our Development Environment:

  • MAC Development Environment Setup

  • WINDOWS Development Environment Setup

  • IDE dbt Extension Installation

  • Creation and Activation of Virtual Environments

  • Setting up Snowflake

Once we are ready - among several other technical topics, the following features will be covered;

  • dbt Models

  • dbt Materializations

  • dbt Tests

  • dbt Documentation

  • dbt Sources, Seeds, Snapshots

  • dbt Hooks and Operations

  • Jinja and Macros

  • dbt Packages

  • Analyses, Exposures

  • dbt Seeds

  • Data Visualization (Preset)

  • Working with Great Expectations (dbt-expectations)

  • Debugging tests in dbt

Once the theory and the practical stages are finished, we are going to dive into the best practices and more advanced topics. The course is continuously updated, whenever dbt publishes an update we adjust the course accordingly, so you always be up to date!

Who is this course for?

  • Data Engineers

  • Data Analysts

  • Data Scientists

  • BI Developers

  • BI Analyst

... and anyone who interacts with data lake/data warehouse/data lakehouse or uses SQL!

Course Level Explained (Zero > Hero)

The course doesn't have any expectations about your abilities and starts education from zero. Every exercise is an unavoidable step in your studies. In the same way, don't start an exercise of a superior level without having completed the preceding ones: you will be in difficulty if you do so. Practice is the only way to learn and it cannot be taken lightly. We are going to be next to you along the journey and you have our absolute support!

When the Airbnb project is presented to you, you have to do it in its entirety, without omitting any guidelines and by understanding the objective. A project "almost completely" done is often a project "totally incomplete" for us. Give special attention to detail. Your only reliable source of information regarding the instructions is the pedagogical team, don't trust the "I've heard".

By the time you complete the course, you will be equipped with both a very solid theoretical understanding and practical expertise with dbt. All the fundamentals, dbt features, best practices, advanced techniques and more will be covered in our course, which will make you become a master in dbt. Are you ready? ;)

How to get help?

We just published our initial round of Discussions on Udemy which is the easiest and most efficient way for you to post questions, receive answers, and peruse questions from other students. If you have questions or feedback, please reach out to us!

That about wraps it up for us for now!


Once again, thank you for being a part of this course.


We can't wait to get started with you soon!

All the best,

Zoltan C. Toth


dbt Mark and the dbt logo are trademarks of dbt Labs, Inc.


Bạn sẽ học được gì

Learn to use the dbt™ platform professionally through the creation of an exhaustive, real-world, hands-on dbt - Airbnb project covering both Theory and Practice

Set up the complete development environment on Mac & Windows, Connect to Snowflake and BI, Configure dbt profile, extend the IDE with dbt tools

Learn core dbt concepts such as Models, Materialization, Sources, Seeds, Snapshots, Packages, Hooks, Exposures, Analyses, write complex SQL queries

Understand the dbt project structure and learn about dbt tips & tricks, advanced techniques and best practices, extend dbt with your own / third-party macros

Implement singular and generic dbt tests, work with additional arguments and default config values, customize dbt built-in tests

Document your models and pipeline, customize the dbt docs page, Explore and analyse dependencies between transformation steps

Understand how dbt fits into the modern data stack, learn about the stages of the Data-Maturity Model, and well functioning Data Architectures

Master ETL/ELT procedures, Data Transformations, Modern Data Stack, Slowly Changing Dimensions, Common Table Expressions and Analytics Engineering

Understand what is a Data Warehouse, Data Lake, or Data Lakehouse and when to use which, handle Data Collection, Data Wrangling and Data Integrations

See how advanced testing works using dbt-expectations, a Great Expectations inspired testing framework

Yêu cầu

  • Basic SQL experience
  • No previous programming language experience required
  • Working computer (Mac/Windows/Linux)
  • Network access whitelist to snowflake(.com) and GitHub if you work behind a firewall or VPN
  • Git and Python (We are linking to the installation instructions of these tools in the course)

Nội dung khoá học

24 sections

Course Introduction

3 lectures
Instructors Introduction
01:23
Welcome
00:47
Course Structure Overview
03:19

Theory - The Data Maturity Model

4 lectures
Introduction - Maslow's Pyramid of Data
02:53
The Data Maturity Model
03:57
ETL and ELT
03:26
The Data Maturity Model
2 questions

Theory - Data Warehouses, Data Lakes and Lakehouses

5 lectures
Data Warehousing - a short introduction
03:34
External Tables and Cloud Data Warehouses
01:42
Data Lakes
01:26
Data Lakehouse
01:05
Data Warehouses, Data Lakes and Lakehouses
2 questions

Theory - The Modern Data Stack

2 lectures
The Modern Data Stack
13:48
The Modern Data Stack
4 questions

Theory - Slowly Changing Dimension (SCD)

6 lectures
The Basics of Slowly Changing Dimensions
01:19
Type 0 - Retain Original
01:07
Type 1 - Overwrite
01:37
Type 2 - Add New Row
02:28
Type 3 - Add New Attribute
02:27
Slowly Changing Dimension (SCD)
2 questions

Intro to the practical sessions: dbt and the Airbnb use-case

2 lectures
dbt Overview
03:44
Use-case and Input Data Model Overview
05:54

Practice - Setup

18 lectures
ESSENTIAL README: How to access course's resources and solution project
00:29
Snowflake Registration
03:37
A note on the Snowflake data import
00:25
Importing Airbnb Data into Snowflake
03:56
READ ME! Setup instructions and Prerequisites
01:54
WINDOWS - Installing Python and pip (optional)
03:09
WINDOWS - Setting up a Python Virtualenv
05:13
MAC - Setting up Python and a Virtualenv
06:24
dbt Installation
03:41
READ ME: Resolving Snowflake Connection Issues
00:46
Creating a dbt project and connecting it to Snowflake using dbt init
07:55
READ ME - Recent changes in dbt (June 2024)
00:33
Overview of the dbt Project Structure
03:24
Free VSCode Extension - Power User for dbt Core (optional)
00:58
Introduction to the Power User for dbt Core VSCode Extension (optional)
01:11
Install and Configure Power User for dbt Core (optional)
06:34
A note on the DEV schema
00:18
Datasets and Data Flow Overview
05:22

Models

7 lectures
Learning Objectives - Models
00:45
Models Overview
00:48
Theory: CTE - Common Table Expressions
03:20
Creating our first model: Airbnb listings
10:53
dbt Power User - Working with Models, Autocomplete and Query Results (optional)
04:16
Models Quiz
1 question
Create the src_hosts model
1 question

Materializations

7 lectures
Learning Objectives - Materializations
00:39
Materializations Overview
04:08
Model Dependencies and dbt's ref tag
10:06
Table type materialization & Project-level Materialization config
03:22
Incremental materialization
07:59
Ephemeral materialization
10:02
Quiz - Materializations
2 questions

Seeds and Sources

5 lectures
Learning Objectives - Seeds and Sources
00:20
Seeds and Sources Overview
00:50
Seeds
05:20
Sources
04:16
Source Freshness
03:05

Snapshots

4 lectures
Learning Objectives - Snapshots
00:39
Snapshots Overview
03:01
Creating a Snapshot
10:10
Snapshots Quiz
1 question

Tests

6 lectures
Learning objectives - Tests
00:25
Tests Overview
02:15
Generic Tests
09:06
Singular Tests
03:10
Create your own singular test
1 question
Tests Quiz
1 question

Macros, Custom Tests and Packages

7 lectures
Learning Objectives - Macros, Custom Tests and Packages
00:33
Macros Overview
00:47
Creating our First Macro
06:21
Writing Custom Generic Tests
02:47
README updated versions of packages
00:38
Installing Third-Party Packages
06:56
Macros, Custom Tests and Packages Quiz
1 question

Documentation

8 lectures
Learning Objectives - Documentation
00:41
Documentation Overview
02:18
Writing and Exploring Basic Documentation
07:32
Markdown-based Docs, Custom Overview Page and Assets
08:41
The Linage Graph (Data Flow DAG)
05:52
dbt Power User - Lineage and Documentation (optional)
05:41
Document the dim_hosts_cleansed table
1 question
Documentation quiz
1 question

Analyses, Hooks and Exposures

7 lectures
Learning Objectives - Analyses, Hook and Exposures
00:44
Analyses
02:31
Hooks
04:18
Setting up a BI Dashboard in Snowflake and Preset
09:38
READ ME - Exposures naming convention changes in recent dbt releases
00:26
Exposures
03:34
Hooks Quiz
1 question

dbt Hero

2 lectures
Welcome to Hero
01:22
Have your say in the course's roadmap
00:13

Debugging Tests and Testing with dbt-expectations

10 lectures
A note on the dbt-expectations setup
00:11
Great Expectations Overview
14:05
Comparing row counts between models
03:34
Looking for outliers in your data
03:11
Implementing test warnings for extremal items
03:40
Validating column types
02:28
Monitoring categorical variables in the source data
04:14
Debugging dbt tests and Working with regular expressions
15:08
dbt-expectations and test debugging quiz
2 questions
Course Feedback and Moving on
1 question

Debugging with Logging

4 lectures
Logging to the dbt Log File
03:21
Logging to the Screen
01:08
Disabling Log Messages
01:50
A short knowledge check
3 questions

Using Variables

6 lectures
Working with Jinja Variables
03:17
A note for Windows users using cmd
00:26
Working with dbt Variables
04:07
Setting Default Values
03:17
Using Date Ranges to Make Incremental Models Production-Ready
05:05
A quick quiz on variables
3 questions

Orchestrating dbt with Dagster

8 lectures
Overview of the Popular dbt Orchestration Tools and how to Choose the Right Tool
14:41
Dagster Installation (All Platforms plus Github Codespace)
04:21
README - Starting Dagster on Windows
00:26
Connecting Dagster to dbt and Starting the Orchestrator
07:01
Deep Dive into the Python Files of our Dagster-dbt Project
12:21
Manage, Orchestrate and Debug your dbt Project with Dagster
10:58
A Note on the Advanced Dagster Section
00:22
Advanced Dagster: Using Partitions with Incremental Models
25:54

Accelerate dbt Development Using Power User for dbt Core

9 lectures
How to Get an API Key for the Advanced Features
03:22
Use AI to Generate Documentation
04:40
Generate dbt Model from Source Definition or SQL
03:22
Working with Column-Level Lineage
02:46
Generate and edit dbt Tests
07:05
Find Problems in your dbt Project with Health Check
03:13
Use AI to Interpret Queries via Query Explanations
01:49
dbt Project Governance
06:39
Query Translation (SQL dialects)
03:30

Best Practices for Introducing and Using dbt in your Company

1 lectures
An interview with the Data Utilization Head of the Vienna Insurance Group
22:04

dbt Certification Exam Preparation Guide

2 lectures
How to prepare for the certification exam? An interview with Muizz Lateef
29:41
Certification Preparation Quiz
80 questions

Supplementary Materials

1 lectures
Supplementary Material - Installing dbt on Windows with Windows Linux Filesystem
10:32

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