The Complete dbt (Data Build Tool) Bootcamp: Zero to Hero
The Complete dbt (Data Build Tool) Bootcamp: Zero to Hero, available at $89.99, has an average rating of 4.6, with 115 lectures, 17 quizzes, based on 5582 reviews, and has 32714 subscribers.
You will learn about 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 Test your knowledge with certification preparation question Listen to real-world use-cases from industry professionals Learn dbt Orchestration Best Practices Hands On This course is ideal for individuals who are Analytics Engineers or Data Analysts or BI Analysts or Data Scientists or Data Engineers It is particularly useful for Analytics Engineers or Data Analysts or BI Analysts or Data Scientists or Data Engineers.
Enroll now: The Complete dbt (Data Build Tool) Bootcamp: Zero to Hero
Summary
Title: The Complete dbt (Data Build Tool) Bootcamp: Zero to Hero
Price: $89.99
Average Rating: 4.6
Number of Lectures: 115
Number of Quizzes: 17
Number of Published Lectures: 115
Number of Published Quizzes: 15
Number of Curriculum Items: 136
Number of Published Curriculum Objects: 134
Original Price: $69.99
Quality Status: approved
Status: Live
What You Will 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
- Test your knowledge with certification preparation question
- Listen to real-world use-cases from industry professionals
- Learn dbt Orchestration Best Practices Hands On
Who Should Attend
- Analytics Engineers
- Data Analysts
- BI Analysts
- Data Scientists
- Data Engineers
Target Audiences
- Analytics Engineers
- Data Analysts
- BI Analysts
- Data Scientists
- Data Engineers
Become a dbt professionalfrom 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 TOP RATED and the BESTSELLER 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!”
New: dbt Certification questions and certification interview!
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 “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.
THEORETICAL SECTION:
Among several other topics, the theoretical section puts special emphasis on transferring knowledge in the following areas;
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Data-Maturity Model
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Well-functioning Data Architectures
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Data Warehouses, Data Lakes, and Data Lakehouses
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ETL and ELT procedures and Data Transformations
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Fundamentals of dbt (Data Build Tool)
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Analytics Engineering
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Modern Data Stack
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Slowly Changing Dimensions
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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:
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MAC Development Environment Setup
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WINDOWS Development Environment Setup
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IDE dbt Extension Installation
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Creation and Activation of Virtual Environments
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Setting up Snowflake
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Using the dbt Power User Visual Studio extension
Once we are ready – among several other technical topics, the following features will be covered;
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dbt Models
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dbt Materializations
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dbt Tests
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dbt Documentation
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dbt Sources, Seeds, Snapshots
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dbt Hooks and Operations
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Jinja and Macros
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dbt Packages
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Analyses, Exposures
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dbt Seeds
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Data Visualization (Preset)
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Working with Great Expectations (dbt-expectations)
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Debugging tests in dbt
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dbt Orchestration
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?
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Data Engineers
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Data Analysts
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Data Scientists
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BI Developers
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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.
Course Curriculum
Chapter 1: Course Introduction
Lecture 1: Instructors Introduction
Lecture 2: Welcome
Lecture 3: Course Structure Overview
Chapter 2: Theory – The Data Maturity Model
Lecture 1: Introduction – Maslow's Pyramid of Data
Lecture 2: The Data Maturity Model
Lecture 3: ETL and ELT
Chapter 3: Theory – Data Warehouses, Data Lakes and Lakehouses
Lecture 1: Data Warehousing – a short introduction
Lecture 2: External Tables and Cloud Data Warehouses
Lecture 3: Data Lakes
Lecture 4: Data Lakehouse
Chapter 4: Theory – The Modern Data Stack
Lecture 1: The Modern Data Stack
Chapter 5: Theory – Slowly Changing Dimension (SCD)
Lecture 1: The Basics of Slowly Changing Dimensions
Lecture 2: Type 0 – Retain Original
Lecture 3: Type 1 – Overwrite
Lecture 4: Type 2 – Add New Row
Lecture 5: Type 3 – Add New Attribute
Chapter 6: Intro to the practical sessions: dbt and the Airbnb use-case
Lecture 1: dbt Overview
Lecture 2: Use-case and Input Data Model Overview
Chapter 7: Practice – Setup
Lecture 1: ESSENTIAL README: How to access course's resources and solution project
Lecture 2: Snowflake Registration
Lecture 3: A note on the Snowflake data import
Lecture 4: Importing Airbnb Data into Snowflake
Lecture 5: READ ME! Setup instructions and Prerequisites
Lecture 6: WINDOWS – Installing Python and pip (optional)
Lecture 7: WINDOWS – Setting up a Python Virtualenv
Lecture 8: MAC – Setting up Python and a Virtualenv
Lecture 9: dbt Installation
Lecture 10: READ ME: Resolving Snowflake Connection Issues
Lecture 11: Creating a dbt project and connecting it to Snowflake using dbt init
Lecture 12: READ ME – Recent changes in dbt (June 2024)
Lecture 13: Overview of the dbt Project Structure
Lecture 14: Free VSCode Extension – Power User for dbt Core (optional)
Lecture 15: Introduction to the Power User for dbt Core VSCode Extension (optional)
Lecture 16: Install and Configure Power User for dbt Core (optional)
Lecture 17: A note on the DEV schema
Lecture 18: Datasets and Data Flow Overview
Chapter 8: Models
Lecture 1: Learning Objectives – Models
Lecture 2: Models Overview
Lecture 3: Theory: CTE – Common Table Expressions
Lecture 4: Creating our first model: Airbnb listings
Lecture 5: dbt Power User – Working with Models, Autocomplete and Query Results (optional)
Chapter 9: Materializations
Lecture 1: Learning Objectives – Materializations
Lecture 2: Materializations Overview
Lecture 3: Model Dependencies and dbt's ref tag
Lecture 4: Table type materialization & Project-level Materialization config
Lecture 5: Incremental materialization
Lecture 6: Ephemeral materialization
Chapter 10: Seeds and Sources
Lecture 1: Learning Objectives – Seeds and Sources
Lecture 2: Seeds and Sources Overview
Lecture 3: Seeds
Lecture 4: Sources
Lecture 5: Source Freshness
Chapter 11: Snapshots
Lecture 1: Learning Objectives – Snapshots
Lecture 2: Snapshots Overview
Lecture 3: Creating a Snapshot
Chapter 12: Tests
Lecture 1: Learning objectives – Tests
Lecture 2: Tests Overview
Lecture 3: Generic Tests
Lecture 4: Singular Tests
Chapter 13: Macros, Custom Tests and Packages
Lecture 1: Learning Objectives – Macros, Custom Tests and Packages
Lecture 2: Macros Overview
Lecture 3: Creating our First Macro
Lecture 4: Writing Custom Generic Tests
Lecture 5: README updated versions of packages
Lecture 6: Installing Third-Party Packages
Chapter 14: Documentation
Lecture 1: Learning Objectives – Documentation
Lecture 2: Documentation Overview
Lecture 3: Writing and Exploring Basic Documentation
Lecture 4: Markdown-based Docs, Custom Overview Page and Assets
Lecture 5: The Linage Graph (Data Flow DAG)
Lecture 6: dbt Power User – Lineage and Documentation (optional)
Chapter 15: Analyses, Hooks and Exposures
Lecture 1: Learning Objectives – Analyses, Hook and Exposures
Instructors
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Zoltan C. Toth
Data Analytics Architecture Expert -
Miklos (Mike) Petridisz
Data Engineer & Solutions Architect Expert
Rating Distribution
- 1 stars: 37 votes
- 2 stars: 63 votes
- 3 stars: 429 votes
- 4 stars: 1921 votes
- 5 stars: 3132 votes
Frequently Asked Questions
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You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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