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  • Book Overview & Buying Data Engineering with dbt
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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

Entity-Relationship modeling

In the previous sections, we briefly defined the three components of an E-R model: entity, attribute, and relationship. We have also seen a few E-R diagrams, drawn with different notations such as UML or crow’s foot.

In this section, we will define in a bit more detail the E-R models and show how different cases can be represented in these two common notations (UML and crow’s foot).

Main notation

We have already introduced the three components of an E-R model. In this section, we explain how they are represented visually in E-R models:

  • Entity: This is represented as a box with the name of the entity inside

If attributes are shown, the entity name is at the top and often in bold or bigger and visually separated from the attributes

  • Attribute: This is represented by the attribute’s name inside the box of the entity it belongs, with one name per line
  • Relationship: This is represented by a line joining...
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Data Engineering with dbt
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