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Fundamentals of Analytics Engineering

You're reading from  Fundamentals of Analytics Engineering

Product type Book
Published in Mar 2024
Publisher Packt
ISBN-13 9781837636457
Pages 332 pages
Edition 1st Edition
Languages
Authors (7):
Dumky De Wilde Dumky De Wilde
Profile icon Dumky De Wilde
Fanny Kassapian Fanny Kassapian
Profile icon Fanny Kassapian
Jovan Gligorevic Jovan Gligorevic
Profile icon Jovan Gligorevic
Juan Manuel Perafan Juan Manuel Perafan
Profile icon Juan Manuel Perafan
Lasse Benninga Lasse Benninga
Profile icon Lasse Benninga
Ricardo Angel Granados Lopez Ricardo Angel Granados Lopez
Profile icon Ricardo Angel Granados Lopez
Taís Laurindo Pereira Taís Laurindo Pereira
Profile icon Taís Laurindo Pereira
View More author details

Table of Contents (23) Chapters

Preface 1. Prologue
2. Part 1:Introduction to Analytics Engineering
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

Summary

In this chapter, you learned how analytics engineers act as the bridge between business, analytics, and data engineering, enabling data democratization through the quality and accessibility of data products. By delivering reliable data models, analytics engineers are a centerpiece of data-informed decisions.

You also learned how the shift from ETL to ELT contributed to the rise of analytics engineering, and how both methods are still applicable currently. Additionally, we discussed how roles can differ across organizations, and how analytics engineers fit in the data supply chain.

In the next chapter, The Modern Data Stack, you will get an overview of the collection of tools and technologies that enable this life cycle, and how this shifted roles and technical barriers in the data landscape.

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