Set up a well-structured data warehouse for your small team in 90 days (Free Guide) https://www.kahandatasolutions.com/guide

You don't have to process every record in a table every time.

Fortunately, dbt offers a great solution for this scenario with the /"incremental/" materialization option.

If set up correctly, you can significantly reduce costs and processing time.

This is because incremental models only process new data and do not recreate an entire table (the default).

However, setting up incremental models is not always easy.

It requires a few steps, an understanding of the underlying functionality, and some customization.

What I'm saying is that I've noticed that this process trips people up and causes them to put off implementing it.

So in today’s video I want to help you by covering the following:
– What incremental models in dbt are all about
– Step by step how to build one
– The process of adding/updating new data

Thank you for watching!

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Time stamp:
0:00 – Introduction
0:27 – What are incremental models?
1:45 – How to use is_incremental()
4:06 – Insert new data
5:31 – Update existing data
6:57 – Dealing with schema changes
9:39 – Using the –full-refresh flag

Title & Tags:
How to create incremental models dbt tutorial
#kahandatasolutions #dataengineering #dbt

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