dbt (data build tool) - Overview for Data Engineering & Modelling

☕️ 𝗕𝘂𝘆 𝗺𝗲 𝗮 𝗰𝗼𝗳𝗳𝗲𝗲: To support the channel and encourage new videos, please consider buying me a coffee here: https://ko-fi.com/bugbytes Top Data Engineer Courses: 📊 Data Engineer in Python - https://datacamp.pxf.io/jeZX5v ⭐Top resource to learn Python - https://datacamp.pxf.io/kOjKkV ⭐ In this video, we'll look at dbt for data engineering - dbt allows you to define SQL models that work together to perform transformations against raw data, materializing the results in your data warehouse/database along the way. We'll look at specific dbt features such as models, sources, Jinja expressions, and documentation. We'll also show how to integrate dbt with Snowflake in this video. 📌 𝗖𝗵𝗮𝗽𝘁𝗲𝗿𝘀: 00:00 Intro to dbt (data build tool) 00:57 Installing dbt-core 02:27 Installing Snowflake Adapter 04:02 Initialising project with “dbt init” command 07:06 “dbt run” command 09:35 Practical example of analytical query using dbt models 13:48 Generating and viewing documentation with dbt 14:48 Adding sources in dbt 18:04 Jinja expressions 22:07 Summary of dbt 𝗦𝗼𝗰𝗶𝗮𝗹 𝗠𝗲𝗱𝗶𝗮: 📖 Blog: https://bugbytes.io/posts/ 👾 Github: https://github.com/bugbytes-io/ 📚 𝗙𝘂𝗿𝘁𝗵𝗲𝗿 𝗿𝗲𝗮𝗱𝗶𝗻𝗴 𝗮𝗻𝗱 𝗶𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻: dbt: https://docs.getdbt.com/docs/introduction Quickstart for Snowflake (and loading data): https://docs.getdbt.com/guides/snowflake?step=1 Snowflake: https://signup.snowflake.com/ #python #dataengineering #datascience #data