Introduction To Dbt: Data Modeling For Analysts

Learn how to use dbt to build custom data models, scale a data warehouse, and develop production-ready data layers.

What you'll learn
How to setup dbt
How to create models in dbt
How to use jinga, variables and table references to build models quickly
How to push models back into a data warehouse
How to use dbt docs to create documentation on the models that have been developed

Requirements
Basic understanding of SQL and databases is required.

Description
Do you want to learn how to build advanced data models within a data warehouse and become more like a data engineer?The Introduction to dbt: Data Modeling for Analysts course will reach you the fundamentals of the dbt platform and walk you through the exact steps needed to turn raw data into powerful business-ready datasets for analyses and dashboards.The course covers the following topics:Getting started with dbt --> How to set up dbt, connect it to your data warehouse and code repository solution.Building your first data models in dbt --> How to navigate the IDE and start writing SQL-based data models.How to leverage jinga, variables and other advanced funtionality within dbt.How to work with Github, set up jobs in dbt, leverage dbt docs and seeds, and more.At the end of the course you will find a 10 question quiz to help you test your knowledge.The course moves at a slow to medium pace allowing you to take in the key concepts and get to know the fundamentals of dbt. Go through the videos in order and build on your knowledge through each lesson.This 3 hour course will give you the knowledge you need to significantly enhance a data warehouse and provide massive value to your employer or clients.

Overview
Section 1: Introduction to dbt

Lecture 1 Getting started with dbt

Lecture 2 Creating our first model in dbt

Lecture 3 Creating our first model in dbt (continued)

Lecture 4 Building the production layer, table references, and our first custom model

Lecture 5 Enhancing our dbt project using jinga and variables

Lecture 6 Merging our code to the main branch, and setting up a job in dbt

Lecture 7 Introduction to dbt docs and persistent docs (BigQuery)

Lecture 8 Introduction to dbt seeds

Lecture 9 Reviewing a complete dbt project (9-figure DTC brand example)

Analysts,Data engineers,Marketers and ops specialists that want to learn how to build data layers in a data warehouse

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