Made easy: Installing dbt and Building Your First Model 'Haay!'

Prequisite: Python and SQL knowledge. Install python and dbt extension on VS code. Steps: open terminal; cd --create python virtual environment python -m venv dbt_venv --activate the env on cmd/powershell .\dbt_venv\Scripts\activate --to deactivate the venv deactivate Installing dbt; in this case I am using dbt-postgresadapter (otherwise free to use other integrations Install with pip), together with dbt core which is an open-source tool that enables data practitioners to transform data and is suitable for users who prefer to manually set up dbt and locally maintain it. python -m pip install dbt-core dbt-postgres add .dbt in the users home directory, user dbt will create and maintain profiles .yml which is the dbt configuration file(db and user creadentials are stored) mkdir $home\.dbt initialize dbt project dbt init and then follow to the command prompts that will appear. Navigate to the project folder that was created: cd dbt_project Verify the connection to your data platform and dbt using: dbt debug command. Create a dbt model; an sql query that is designed to perform a certain transformation task on the data platform. It's important to note dbt makes use of CTEs for improved readability and modularity. create a .sql file, and making use of CTEs and save. To run the model use: dbt run which creates a view in your data platform with the same name as the model. Its also important to note that at the end of the .yml file, the default materialization for dbt models is a view and can be updated to a table either at the .yml file or at the model Updating materialization on the model; {{ config(materialized = 'table')}}.

May 12, 2025 - 21:31

Made easy: Installing dbt and Building Your First Model 'Haay!'

Prequisite: Python and SQL knowledge.
Install python and dbt extension on VS code.
Steps:
open terminal;
cd

--create python virtual environment
python -m venv dbt_venv

--activate the env on cmd/powershell
.\dbt_venv\Scripts\activate

--to deactivate the venv
deactivate

Installing dbt; in this case I am using dbt-postgresadapter (otherwise free to use other integrations Install with pip),
together with dbt core which is an open-source tool that enables data practitioners to transform data and is suitable for users who prefer to manually set up dbt and locally maintain it.

python -m pip install dbt-core dbt-postgres

add .dbt in the users home directory, user dbt will create and maintain profiles .yml which is the dbt configuration file(db and user creadentials are stored)
mkdir $home\.dbt

initialize dbt project
dbt init and then follow to the command prompts that will appear.

Navigate to the project folder that was created:
cd dbt_project
Verify the connection to your data platform and dbt using:
dbt debug command.

Create a dbt model; an sql query that is designed to perform a certain transformation task on the data platform.
It's important to note dbt makes use of CTEs for improved readability and modularity.

create a .sql file, and making use of CTEs and save.
To run the model use:
dbt run
which creates a view in your data platform with the same name as the model.

Its also important to note that at the end of the .yml file,
the default materialization for dbt models is a view and can be updated to a table either at the .yml file or at the model

Updating materialization on the model;
{{ config(materialized = 'table')}}.