What you'll learn
Connect DBT to Snowflake or another database
Create SQL transformations that use consistent logic
Test SQL transformations and underlying data
Run transformations on a schedule
Add snapshots for slowly changing dimensional tables
Test your code in a dev environment
Learn DBT Best Practices
Advanced DBT Topics
Requirements
SQL
Github
Ability to work in the command line
Description
What you'll learn
Welcome to this course, Learn DBT from Scratch. DBT lets you build a system of transformations on your data, with tests, scheduled runs, multiple environments, flexibility, and more all without needing a team of engineers to set up and manage your workflow. By the end of this course, you will have:
set up DBT locally and on the cloud
connected DBT to Snowflake (or a data warehouse of your choice)
create your own SQL transformations on data
test your transformations
snapshot your data to keep track of how your data changes over time
learn DBT best practices
In this course, you'll be presented with the summarized information you need so that you can quickly get DBT implemented in your data pipeline (or in a brand new, data warehouse).
Why you should learn DBT
DBT is not one of the first technical skills most Data Scientists or Analysts think to learn. It's not as exciting as machine learning algorithms, and it's not as easy to show off as a fancy data visualization.
But DBT is an absolutely fundamental skill for any Data Scientist or Analyst due to all of its capabilities. Because DBT is so flexible, there are almost an endless amount of ways you can integrate DBT into your data architecture. Some features that DBT provides you that all Data Scientists and Analysts should be using in their work include:
Creating consistent aggregations for your analysis in a single location
Consistently testing your transformations and underlying data
Running your data transformations on a schedule
Test your code in a DEV environment
About DBT
DBT is pioneering modern analytics engineering. DBT applies the principles of software engineering to analytics code, an approach that dramatically increases your leverage as a data analyst. They believe that data analysts are the most valuable employees of modern, data-driven businesses and they build tools that empower analysts to own the entire analytics engineering workflow.
Who this course is for:
Data Analysts and Scientists looking to improve their data pipeline
Prospective Data Scientists and Analysts interested in learning data engineering
Data Analytics Managers looking to understand the capabilities of DBT

Homepage

https://www.udemy.com/course/learn-dbt-from-scratch/

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