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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

Summary

In this chapter, we transitioned from theory to practice by focusing on analytics engineering in a real-world context. The Stroopwafelshop case study guided you in assisting the store’s owner, Jan, with understanding and analyzing his business data. This case study served as a practical example, demonstrating how to apply analytics engineering techniques and tools in a business context.

Powerful tools such as Airbyte Cloud, Google BigQuery, dbt Cloud, and Tableau were introduced and used. This hands-on approach has not only equipped you with the necessary skills to tackle real-life analytics engineering challenges but also culminated in the creation of an insightful dashboard for the Stroopwafelshop. This combination of theory and practice has offered a glimpse into the daily activities of an analytics engineer, underscoring the importance of comprehending metrics and KPIs to add value to the business.

In the next chapter, you will delve into the importance of...

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