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Data Engineering with dbt

Data Engineering with dbt

By : Roberto Zagni
4.6 (9)
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Data Engineering with dbt

Data Engineering with dbt

4.6 (9)
By: Roberto Zagni

Overview of this book

dbt Cloud helps professional analytics engineers automate the application of powerful and proven patterns to transform data from ingestion to delivery, enabling real DataOps. This book begins by introducing you to dbt and its role in the data stack, along with how it uses simple SQL to build your data platform, helping you and your team work better together. You’ll find out how to leverage data modeling, data quality, master data management, and more to build a simple-to-understand and future-proof solution. As you advance, you’ll explore the modern data stack, understand how data-related careers are changing, and see how dbt enables this transition into the emerging role of an analytics engineer. The chapters help you build a sample project using the free version of dbt Cloud, Snowflake, and GitHub to create a professional DevOps setup with continuous integration, automated deployment, ELT run, scheduling, and monitoring, solving practical cases you encounter in your daily work. By the end of this dbt book, you’ll be able to build an end-to-end pragmatic data platform by ingesting data exported from your source systems, coding the needed transformations, including master data and the desired business rules, and building well-formed dimensional models or wide tables that’ll enable you to build reports with the BI tool of your choice.
Table of Contents (21 chapters)
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1
Part 1: The Foundations of Data Engineering
7
Part 2: Agile Data Engineering with dbt
14
Part 3: Hands-On Best Practices for Simple, Future-Proof Data Platforms

Working with Git in dbt Cloud

When working with dbt Cloud, you must have a Git repository to store your code.

You can use your own Git providers, such as GitHub, GitLab, Azure DevOps, Bitbucket, or others that implement the standard HTTPS or SSH Git communication interfaces. If you do not have a Git provider, dbt Cloud can use and internally manage the open source Git implementation.

It is important to note that branch and merge are Git concepts and are, therefore, always available, while PRs are totally external to Git and are a collaborative tool developed and powered by the individual Git provider.

If you use one of the Git providers that dbt Cloud has developed an integration for, (currently GitHub, GitLab, and Azure DevOps), you will already have PRs configured and a Continuous Integration (CI) process available when you open or propose a change to a PR.

In all other cases, to use PRs you just need to configure the correct URL so that dbt Cloud allows you to open a...

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