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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
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Part 1:Introduction to Analytics Engineering
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Chapter 1: What Is Analytics Engineering?
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Part 2: Building Data Pipelines
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Chapter 7: Serving Data
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Part 3: Hands-On Guide to Building a Data Platform
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Part 4: DataOps
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Part 5: Data Strategy
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Chapter 12: Driving Business Adoption
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Index
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Applying data governance in analytics engineering

So far, the concept of data governance might feel overwhelming or a bit fuzzy. If so, there is no need to worry. Nobody is going to ask you for a textbook definition. In fact, nobody else in your team may have ever heard of governance.

Nevertheless, even if they do not call by its name, your colleagues will often discuss the issues caused by poor governance. They will talk about how much time they waste cleaning data or their frustration when nobody fixes data quality at the source. For this reason, from now on, we will talk about governance in the way that most people understand: highlighting its main topics and demonstrating how they are relevant to your work.

Governance is interwoven into your role as an analytics engineer, especially if enabling data analysts and other data consumers is among your responsibilities. In this section, we will provide a comprehensive overview of the essential elements that data teams need to consider...

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