The Data Bootcamp: Transform your Data using dbt™
Learn dbt™ from scratch. Build data models, perform testing, generate documents & become an all rounded Data Engineer!
What you will learn
Learn how to use dbt end-to-end through a realistic project, hands-on project
Learn the fundamentals of dbt including connecting to a data warehouse, developing models, working with sources, creating tests, deploying and much more
Understand how dbt is beneficial in a modern data stack and how the Extract, Load and Transform process works
Learn how to use Macros and Packages in dbt to simplify and reuse your code
Learn how dbt can work with complex SQL queries
Perform Testing in dbt such as singular tests, generic tests and source testing
Develop documentation for your models, understand modularity and dependancies in dbt
Learn about the dbt Project Structure and how to set up your own project
Understand how to use JINJA in dbt
Learn how to deploy in dbt under a schedule and investigate run time errors
Learn how to use Seeds and Analysis in dbt
Are you looking for a cutting-edge way to extract load and transform your data? Do you want to know more about dbt™ and how to use it? Well, this is the course for you. Welcome to The dbt™ Bootcamp: Transform your Data using dbt™.
In this course you are going to learn all about dbt™, from setting up dbt™ cloud, connecting it to Snowflake or a warehouse of your choice, developing models, creating sources, doing testing, working with the documentation and much more.
This course is for beginners, we will go through a realistic project and cover each of the steps mentioned in a practical approach.
dbt™ is a data modelling tool that makes life much easier for analysts and engineers. It allows you to write SQL queries without having to worry about dependencies. dbt™, like traditional databases, is built on SQL, but it has additional functionality built on top of it utilizing templating engines such as JINJA.
This effectively lets you to retrieve, rearrange, and organize your data using additional logic in your SQL. You may then compile and run this code using dbt's™ run command to retrieve just the pieces you need in the transformations. It can also be swiftly coded, tested, and adjusted without having to wait for it to process all your data. In addition to that, it’s automated documentation is a big time saver.
The project we will be working on is about a fictitious company called GlobalMart. GlobalMart sells household items like furniture, office equipment, Appliances and Electronics. They are in the process of hiring a small data team and would like to try out dbt™ for their data transformations. They require some reporting tables about their profits and want to use dbt™ to transform their data to get them what they want.
By the end of this course, we will work through the project and end up accomplishing the following:
1. Setting up a dbt™ Cloud Account
2. Connecting to a Database (in this case Snowflake)
3. Connecting dbt™ to a repository like GitHub
4. Understanding the dbt™ cloud interface
5. Building and Running Models in dbt™
6. Using Modularity in dbt™
7. Creating and Referencing Sources
8. Performing Tests in dbt™ including Singular and Generic Tests
9. How to Create and Generate Documentation in dbt™
10. How to Deploy in dbt™
11. How to use Jinja
12. Using Macros and Packages in dbt™
13. Using Seeds and Analyses in dbt™
This is a great, comprehensive which will really up-skill you not only in dbt but the extract, load and transform process as well.
Thank you so much for choosing this course and I’ll see you in the next lecture.