1. Introducing dbt
Welcome back! Let's now take a look at some more details about dbt and the kind of projects it's used with.
2. dbt defined
dbt, also known as the data build tool, is designed to simplify the management of data warehouses and transform the data within. This is primarily the T, or transformation, within ELT (or sometimes ETL) processes.
It allows for easy transition between data warehouse types, such as Snowflake, BigQuery, Postgres, or in this course, DuckDB.
dbt also provides the ability to use SQL across teams of multiple users, simplifying interaction. In addition, dbt translates between SQL dialects as appropriate to connect to different data sources and warehouses.
3. What does dbt do?
dbt mainly uses SQL to define data models and transform them. Here, a data model is just a way to organize your data. For example, it might organize your data into tables, views, or other database objects, and defines the relationships between them. For example, in an e-commerce context, a data model might link sales data to product details, and payment records. Such a data model allows for efficient analysis and reporting. As such, you should be fairly knowledgeable of SQL to get the most out of using dbt.
dbt can define the relationships between data models and manage the dependencies that arise when using them. Consider if we had one model for customers and a second for orders; these can be linked easily with dbt.
The dbt tool also performs the transformation process (or processes) as defined by the user. A basic example is converting the raw data from log files into database tables.
Finally, dbt can also test and verify the data matches user-defined quality requirements. We'll cover all of these in later videos.
4. What does dbt look like?
dbt is open-source, also known as dbt-core, primarily available as a command-line tool, available for all main operating systems such as Mac, Windows, and Linux.
There is also a managed version of dbt known as dbt Cloud that we won't cover in this course.
dbt and has many commands and sub commands we'll cover later. For now the two commands we need are dbt version and dbt -h for help.
5. Who is dbt for?
As we've discussed what dbt is, we should also mention who it's designed for. Typically dbt is used by anyone that needs to transform raw data in a warehouse prior to use (using SQL). This can include Data Engineers, Analytics Engineers (a cross between data engineers and analysts), and Data Analysts.
6. Let's practice!
Now, let's practice what we've learned in the exercises ahead.