Complete guide to Learning DBT including connecting it to a Data Warehouse
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
- SQL
- Github
- Ability to work in the command line
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
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
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
