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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

What Is Analytics Engineering?

In the era of modern data warehousing, the landscape for data teams saw a radical transformation. With affordable storage and the growing popularity of Extract, Load, and Transform (ELT), a new breed of data teams has emerged. No longer dependent solely on data engineers for warehouse management and data transformation, these teams seek to bridge the gap between engineering and business. This change resulted in the rise of a specialized role – the analytics engineer.

The first written mention of the term analytics engineer appeared in early 2019. Since then, the field of analytics engineering has grown in popularity, demand, and standards.

In this chapter, you will learn what an analytics engineer does and how they can contribute to a solid data strategy. Additionally, we will discuss the shift from Extract, Transform, and Load (ETL) to ELT and the difference between the work of data analysts, data engineers, and analytics engineers.

The...

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