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Fundamentals of Analytics Engineering

You're reading from   Fundamentals of Analytics Engineering An introduction to building end-to-end analytics solutions

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Product type Paperback
Published in Mar 2024
Publisher Packt
ISBN-13 9781837636457
Length 332 pages
Edition 1st Edition
Tools
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Authors (7):
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Dumky De Wilde Dumky De Wilde
Author Profile Icon Dumky De Wilde
Dumky De Wilde
Ricardo Angel Granados Lopez Ricardo Angel Granados Lopez
Author Profile Icon Ricardo Angel Granados Lopez
Ricardo Angel Granados Lopez
Lasse Benninga Lasse Benninga
Author Profile Icon Lasse Benninga
Lasse Benninga
Taís Laurindo Pereira Taís Laurindo Pereira
Author Profile Icon Taís Laurindo Pereira
Taís Laurindo Pereira
Jovan Gligorevic Jovan Gligorevic
Author Profile Icon Jovan Gligorevic
Jovan Gligorevic
Juan Manuel Perafan Juan Manuel Perafan
Author Profile Icon Juan Manuel Perafan
Juan Manuel Perafan
Fanny Kassapian Fanny Kassapian
Author Profile Icon Fanny Kassapian
Fanny Kassapian
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Table of Contents (23) Chapters Close

Preface 1. Prologue
2. Part 1:Introduction to Analytics Engineering FREE CHAPTER
3. Chapter 1: What Is Analytics Engineering? 4. Chapter 2: The Modern Data Stack 5. Part 2: Building Data Pipelines
6. Chapter 3: Data Ingestion 7. Chapter 4: Data Warehousing 8. Chapter 5: Data Modeling 9. Chapter 6: Transforming Data 10. Chapter 7: Serving Data 11. Part 3: Hands-On Guide to Building a Data Platform
12. Chapter 8: Hands-On Analytics Engineering 13. Part 4: DataOps
14. Chapter 9: Data Quality and Observability 15. Chapter 10: Writing Code in a Team 16. Chapter 11: Automating Workflows 17. Part 5: Data Strategy
18. Chapter 12: Driving Business Adoption 19. Chapter 13: Data Governance 20. Chapter 14: Epilogue 21. Index
22. Other Books You May Enjoy

Tools that facilitate data transformations

As data volumes, complexity, and usage continue to grow, tools that facilitate data transformations have emerged to simplify and streamline this process. During the early 2020s, dbt became one of the most prominent and used tools for data transformation.

These tools have revolutionized the way data engineers and analysts work, making it easier and more efficient to transform and analyze data. Previously, data transformations consisted of a series of files containing SQL queries, requiring extensive coding and scripting to ensure they ran in the desired order.

Now, most tools can transform data, sometimes with low or even no code. However, the fact that you can doesn’t mean that you should. Most of the time, the answer to whether you should transform data in a tool is “it depends.” The following section explores what to consider when making that decision.

Types of transformation tools

As seen in the Where to...

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