The Complete dbt (Data Build Tool) Bootcamp: Zero to Hero

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Zoltan C. Toth,Miklos (Mike) Petridisz

6:38:05

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01 - Course Introduction

001 Instructors Introduction.mp4

01:23

002 Welcome.mp4

00:47

003 Complete-dbt-Bootcamp-slides.pdf

003 Course Structure Overview.mp4

03:19

02 - Theory - The Data Maturity Model

001 Introduction - Maslows Pyramid of Data.mp4

02:53

002 The Data Maturity Model.mp4

03:57

003 ETL and ELT.mp4

03:26

03 - Theory - Data Warehouses, Data Lakes and Lakehouses

001 Data Warehousing - a short introduction.mp4

03:34

002 External Tables and Cloud Data Warehouses.mp4

01:42

003 Data Lakes.mp4

01:26

004 Data Lakehouse.mp4

01:05

04 - Theory - The Modern Data Stack

001 The Modern Data Stack.mp4

13:48

05 - Theory - Slowly Changing Dimension (SCD)

001 The Basics of Slowly Changing Dimensions.mp4

01:19

002 Type 0 - Retain Original.mp4

01:07

003 Type 1 - Overwrite.mp4

01:37

004 Type 2 - Add New Row.mp4

02:28

005 Type 3 - Add New Attribute.mp4

02:27

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

001 dbt Overview.mp4

03:44

002 Use-case and Input Data Model Overview.mp4

05:54

07 - Practice - Setup

001 How to use github and the courses resources.html

002 Snowflake Registration.mp4

03:37

003 A note on the Snowflake data import.html

004 010-snowflake-setup.zip

004 Importing Airbnb Data into Snowflake.mp4

03:56

005 READ ME! Setup instructions and Prerequisites.html

006 Optional - Installing Python and pip on Windows.mp4

03:09

007 Optional - Setting up a Python Virtualenv on Windows.mp4

05:13

008 Optional - Setting up Python and pip on a Mac.mp4

06:24

009 dbt Installation (All Platforms).mp4

01:58

010 Creating a dbt 1.5 project and connecting it to Snowflake using dbt init.mp4

07:55

011 READ ME - dbt project structure - data folder vs. seeds folder.html

012 Overview of the dbt Project Structure.mp4

03:24

013 The dbt Power User Extension for VSCode.html

014 Introduction to the dbt Power User VSCode Extension (optional).mp4

01:11

015 Install and Configure the dbt Power User Extension (optional).mp4

04:16

016 A note on the DEV schema.html

017 Datasets and Data Flow Overview.mp4

05:22

external-links.txt

08 - Models

001 Learning Objectives - Models.mp4

00:45

002 Models Overview.mp4

00:48

003 Theory CTE - Common Table Expressions.mp4

03:20

004 Creating our first model Airbnb listings.mp4

10:53

004 Models.md.pdf

005 dbt Power User - Working with Models, Autocomplete and Query Results.mp4

04:16

09 - Materializations

001 Learning Objectives - Materializations.mp4

00:39

002 Materializations Overview.mp4

04:08

003 Materializations.md.pdf

003 Model Dependencies and dbts ref tag.mp4

10:07

004 Table type materialization & Project-level Materialization config.mp4

03:22

005 Incremental materialization.mp4

07:59

006 Ephemeral materialization.mp4

10:02

10 - Seeds and Sources

001 Learning Objectives - Seeds and Sources.mp4

00:20

002 Seeds and Sources Overview.mp4

00:50

003 Seeds.mp4

05:20

003 Sources-and-Seeds.pdf

003 seed-full-moon-dates.csv

004 Sources.mp4

04:16

005 Source Freshness.mp4

03:05

11 - Snapshots

001 Learning Objectives - Snapshots.mp4

00:39

002 Snapshots Overview.mp4

03:01

003 Creating a Snapshot.mp4

10:10

003 Snapshots.md.pdf

12 - Tests

001 Learning objectives - Tests.mp4

00:25

002 Tests Overview.mp4

02:15

003 Generic Tests.mp4

09:06

003 Tests.md.pdf

004 Singular Tests.mp4

03:10

13 - Macros, Custom Tests and Packages

001 Learning Objectives - Macros, Custom Tests and Packages.mp4

00:33

002 Macros Overview.mp4

00:47

003 Creating our First Macro.mp4

06:22

003 Macros-CustomTests-Packages.md.pdf

004 Writing Custom Generic Tests.mp4

02:47

005 README updated versions of packages.html

006 Installing Third-Party Packages.mp4

06:56

14 - Documentation

001 Learning Objectives - Documentation.mp4

00:41

002 Documentation Overview.mp4

02:19

003 Documentation.md.pdf

003 Writing and Exploring Basic Documentation.mp4

07:33

004 Markdown-based Docs, Custom Overview Page and Assets.mp4

08:41

004 input-schema.zip

005 The Linage Graph (Data Flow DAG).mp4

05:52

006 dbt Power User - Lineage and Documentation.mp4

05:41

15 - Analyses, Hooks and Exposures

001 Learning Objectives - Analyses, Hook and Exposures.mp4

00:45

001 analyses-hooks-exposures.pdf

002 Analyses.mp4

02:31

003 Hooks.mp4

04:18

004 Setting up a BI Dashboard in Snowflake and Preset.mp4

05:55

005 Exposures.mp4

03:34

16 - dbt Hero

001 Welcome to Hero.mp4

01:22

002 Have your say in the courses roadmap.html

17 - Debugging Tests and Testing with dbt-expectations

001 A note on the dbt-expectations setup.html

002 Great Expectations Overview.mp4

14:05

002 great-expectations.pdf

003 Comparing row counts between models.mp4

03:34

004 Looking for outliers in your data.mp4

03:11

005 Implementing test warnings for extremal items.mp4

03:40

006 Validating column types.mp4

02:28

007 Monitoring categorical variables in the source data.mp4

04:14

008 Debugging dbt tests and Working with regular expressions.mp4

15:08

18 - Accelerate dbt Development Using dbt Power User

001 How to Get an API Key for the Advanced Features.mp4

05:42

002 Use AI to Generate Documentation.mp4

04:40

003 Generate dbt Model from Source Definition or SQL.mp4

03:22

004 Working with Column-Level Lineage.mp4

02:46

005 Find Problems in your dbt Project with Health Check.mp4

03:13

006 Use AI to Interpret Queries via Query Explanations.mp4

01:49

19 - Best Practices for Introducing and Using dbt in your Company

001 An interview with the Data Utilization Head of the Vienna Insurance Group.mp4

22:05

20 - dbt Certification Exam Preparation Guide

001 How to prepare for the certification exam An interview with Muizz Lateef.mp4

29:42

001 quiz.pdf

21 - Supplementary Materials

001 Supplementary Material - Installing dbt on Windows with Windows Linux Filesystem.mp4

10:32

Description

Become a dbt professional with this ALL-IN-ONE COURSE covering both theory & practice through a real-world project!

What You'll Learn?

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

Who is this for?

Analytics Engineers

Data Analysts

BI Analysts

Data Scientists

Data Engineers

What You Need to Know?

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)

More details

Description
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. This is the MOST COMPLETE, CONTINUOUSLY UPDATED independent dbt (Data Build Tool) software course in the world - as of 2024!
This course is the TOPÂ RATEDÂ and the BESTSELLERÂ dbt course on Udemy!

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

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 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 will shift to the technicalities - a practical section - which will focus on putting together the dbt â€œpuzzleâ€. 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.

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 understand the theoretical layer and how dbt fits into the picture, we will start building out a dbt project from scratch, just as you would do 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
Using the dbt Power User Visual Studio extension
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 will 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 has no 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 completing 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 will be next to you along the journey and you have our absolute support!
When the Airbnb project is presented to you, you must do it entirely, 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 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.

Who this course is for:
Analytics Engineers
Data Analysts
BI Analysts
Data Scientists
Data Engineers

User Reviews

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I help global companies build web-scale data analytics and AI systems. Backed by 20 years of experience in developing data-intensive applications, I spend most of my time helping companies kick-off and mature their data analytics and AI infrastructure, and give Cloud, Apache Spark, Databricks and MLOps courses regularly.Earlier I built Prezi's big data analytics infrastructure, later led Prezi’s data engineering team, scaling it to serve 60 million users backed by a data volume over a petabyte. I also worked on kicking off the Spark integration component in RapidMiner, a global leader in predictive analytics.Besides working with data analytics architectures, I enjoy teaching at Central European University, one of the best independent universities in Europe, and delivering courses and professional services engagements on behalf of Databricks, the company created by the original authors of Spark.

Miklos (Mike) Petridisz

Instructor's Courses

I work as an Expert Data Engineer and Solutions Architect. In parallel, I am a Real-time Data Processing, Big Data & Cloud Computing, Data Platform, and Use Case Seminar TA of Zoltan’s data courses at Central European University, one of the best independent universities in Europe. I used to work as a Senior Data Engineer and Technical Instructor at Databricks, and as a Data Engineering Consultant at Datapao - a Data and Cloud service company covering data and cloud transformation journeys from enablement through architecture to implementation. I have experience developing data-intensive applications, data infrastructures, data platforms, handling cloud migrations, and delivering technical courses on behalf of Datapao, and Databricks - the original creators of Apache Spark. I co-founded NordQuant with Zoltan C. Toth, a company under which we create top-notch dbt (Data Build Tool) and other technical courses.

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