Introduction to dbt

In this course we will learn about dbt, the open source tool that is used for data transformations in relational data warehouses. Though dbt is more commonly found against traditional data warehouses, it still potentially serves a useful purpose as part of your ClickHouse deployment.

Program:
23 Lessons
Level:
Beginner
Total Time:
7h 15m
Lesson overview:
01

Introduction To dbt

In this lesson we will introduce dbt and the value it brings to data teams.

0h 15m
02

Introduction To Testing With dbt

In this lesson we will introduce the various ways in which dbt supports testing as part of a data pipeline.

0h 15m
03

Benefits Of dbt

In this lesson we will explain the benefits of dbt and the problems with the existing approach;

0h 15m
04

Defining Tests As Properties

In this lesson we will show how to define static tests as dbt properties.

0h 15m
05

Using The dbt Command Line Interface

In this lesson we will use the dbt Command Line Interface to create and configure our first dbt project.

0h 15m
06

Creating A dbt Project

In this lesson we will use the dbt Command Line Interface to create and configure our first dbt project.

0h 15m
07

Singular Tests

In this lesson we will explain the dbt concept of singular tests.

0h 15m
08

Generic Tests

In this lesson we will introduce generic tests.

0h 15m
09

Configuring dbt Profiles

In this lesson we will explain the dbt profile system and best practices for managing profiles for maintainable code.

0h 15m
10

Executing Your First Transformations

In this lesson we will create and run our first transformations using dbt models that build both tables and views.

0h 15m
11

Linting Your dbt Code

In this lesson we will introduce the concept linting and learn how it can be used to improve the quality of your dbt code.

0h 15m
12

Materialisation Options and Considerations

In this lesosn we will describe the options and considerations when materialising models in dbt.

2h 45m
13

Materialising As Views and Tables

In this lesson we will use dbt to materialise to tables and views, and the associated incremental and ephemeral options.

0h 15m
14

Testing Sources

In this lesson we will learn how to test source data with dbt.

0h 15m
15

Seed Data

In this lesson we will use dbts seed data feature to reliably populate our database with static data for use as part of dbt transformations.

0h 15m
16

Testing Seed Data

In this lesson we will learn how to test source data with dbt.

0h 15m
17

Testing With dbt

In this lesson we will use the testing features of dbt to validate data transformations and pipelines.

0h 15m
18

Incremental Views

In this lesson we will learn about dbts incremental updates and incremental views.

0h 15m
19

Ethemeral Views

In this lesson we will learn about dbts ethemeral view feature to improve your pipeline readability.

0h 15m
20

Sources and Exposures

In this lesson we will learn about dbts source and exposure features to capture better metadata regarding your pipelines.

0h 15m
21

Documenting Your Models

In this lesson we will learn about dbts features for automatically generating documentation.

0h 15m
22

dbt Cloud

In this lesson will will explain dbt cloud and the value that it brings.

0h 15m
23

dbt and DevOps

In this lesson we will explain how dbt helps Data Engineers work like software engineers.

0h 15m
Benjamin Wootton
Your Course Curator

Benjamin Wootton

Ensemble Founder

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