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Fundamentals of Analytics Engineering
By :

Fundamentals of Analytics Engineering
By:
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)
Preface
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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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Chapter 2: The Modern Data Stack
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Part 2: Building Data Pipelines
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Chapter 3: Data Ingestion
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Chapter 4: Data Warehousing
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Chapter 5: Data Modeling
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Chapter 6: Transforming Data
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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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Chapter 8: Hands-On Analytics Engineering
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Part 4: DataOps
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Chapter 9: Data Quality and Observability
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Chapter 10: Writing Code in a Team
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Chapter 11: Automating Workflows
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Part 5: Data Strategy
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Chapter 12: Driving Business Adoption
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Chapter 13: Data Governance
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Chapter 14: Epilogue
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Index
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