โ๏ธ ๐๐๐ ๐บ๐ฒ ๐ฎ ๐ฐ๐ผ๐ณ๐ณ๐ฒ๐ฒ:
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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.
๐ ๐๐ต๐ฎ๐ฝ๐๐ฒ๐ฟ๐:
00:00 Intro to dbt (data build tool)
00:57 Installing dbt-core
02:27 Installing Snowflake Adapter
04:02 Initialising project with โdbt initโ command
07:06 โdbt runโ 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
๐ฆ๐ผ๐ฐ๐ถ๐ฎ๐น ๐ ๐ฒ๐ฑ๐ถ๐ฎ:
๐ Blog: https://bugbytes.io/posts/
๐พ Github: https://github.com/bugbytes-io/
๐ ๐๐๐ฟ๐๐ต๐ฒ๐ฟ ๐ฟ๐ฒ๐ฎ๐ฑ๐ถ๐ป๐ด ๐ฎ๐ป๐ฑ ๐ถ๐ป๐ณ๐ผ๐ฟ๐บ๐ฎ๐๐ถ๐ผ๐ป:
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