🧱 dbt (Data Build Tool) Flashcards
dbt (Data Build Tool) is an open-source framework that transforms raw warehouse data into reliable datasets.
It empowers teams to use SQL, version control, and modular design.
In addition, dbt helps analysts adopt software engineering best practices.
Below are quick flashcards to guide your learning.
⚙️ What is dbt?
dbt is an open-source tool for data transformation. It lets analysts and engineers use SQL with version control to build trusted pipelines.
🧠 What language powers dbt?
dbt is built in Python. However, its transformations are written in SQL enhanced with Jinja templating.
🏗️ What are dbt models?
Models are SQL files that define transformations. Each model is a SELECT statement materialized as a table or view.
🔁 What is materialization?
Materializations define how models persist — as views, tables, incremental tables, or ephemeral temporary tables.
🧪 What are tests in dbt?
Tests validate data quality. For example, they check for nulls, uniqueness, referential integrity, and custom assertions.
📦 What is a dbt project?
A dbt project is a folder structure containing models, tests, macros, and the
dbt_project.yml configuration.📜 What is dbt run?
dbt run builds your transformations by executing all models in the order defined by their dependency graph.📊 What is dbt DAG?
dbt automatically builds a directed acyclic graph (DAG) of dependencies. This ensures models execute in the right order.
🔍 What are sources?
Sources represent raw tables in your warehouse. You typically reference them in models using
source().💡 What is Jinja in dbt?
Jinja is a templating engine. It adds logic such as loops and variables into SQL models, making pipelines flexible.
For deeper learning, check out the official
dbt documentation
or the dbt GitHub repository.
You can also explore our Uplatz Blog
for more data engineering tutorials.