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Fundamentals of Analytics Engineering

Fundamentals of Analytics Engineering

By : Dumky De Wilde, Kassapian, Gligorevic, Juan Manuel Perafan, Lasse Benninga, Ricardo Angel Granados Lopez, Taís Laurindo Pereira
4.7 (3)
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Fundamentals of Analytics Engineering

Fundamentals of Analytics Engineering

4.7 (3)
By: Dumky De Wilde, Kassapian, Gligorevic, Juan Manuel Perafan, Lasse Benninga, Ricardo Angel Granados Lopez, Taís Laurindo Pereira

Overview of this book

Written by a team of 7 industry experts, Fundamentals of Analytics Engineering will introduce you to everything from foundational concepts to advanced skills to get started as an analytics engineer. After conquering data ingestion and techniques for data quality and scalability, you’ll learn about techniques such as data cleaning transformation, data modeling, SQL query optimization and reuse, and serving data across different platforms. Armed with this knowledge, you will implement a simple data platform from ingestion to visualization, using tools like Airbyte Cloud, Google BigQuery, dbt, and Tableau. You’ll also get to grips with strategies for data integrity with a focus on data quality and observability, along with collaborative coding practices like version control with Git. You’ll learn about advanced principles like CI/CD, automating workflows, gathering, scoping, and documenting business requirements, as well as data governance. By the end of this book, you’ll be armed with the essential techniques and best practices for developing scalable analytics solutions from end to end.
Table of Contents (23 chapters)
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1
Prologue
Free Chapter
2
Part 1:Introduction to Analytics Engineering
5
Part 2: Building Data Pipelines
11
Part 3: Hands-On Guide to Building a Data Platform
13
Part 4: DataOps
17
Part 5: Data Strategy
21
Index

To get the most out of this book

Familiarity with Python and SQL will enhance comprehension of Chapters 8, 10, and 11. Additionally, basic knowledge of command-line usage (with tools such as Git and dbt) and familiarity with cloud computing concepts will be beneficial, as this book serves as an introduction to these topics.

The following software/hardware are covered in the book:

Software/Hardware are covered in the book

Operating system requirement

Airbyte Cloud

WindowsOS, macOS, or Linux

dbt Cloud

Google Cloud, Google BigQuery, Google Sheets

Tableau Desktop

Git and GitHub

Some of these tools have paid versions. To follow the instructions in this book, you can use the free versions or make use of a free trial.

If you are using the digital version of this book, we advise you to type the code yourself or access the code from the book’s GitHub repository (a link is available in the next section). Doing so will help you avoid any potential errors related to the copying and pasting of code.

Several chapters in the book feature code snippets designed to showcase best practices. However, executing these snippets may need extra setup, not covered in this book. You should view these snippets as illustrative examples and adapt the underlying best practices to your unique scenarios.

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