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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
Prologue
Part 1:Introduction to Analytics Engineering
Chapter 1: What Is Analytics Engineering?
Chapter 2: The Modern Data Stack
Part 2: Building Data Pipelines
Chapter 3: Data Ingestion
Chapter 4: Data Warehousing
Chapter 5: Data Modeling
Chapter 6: Transforming Data
Chapter 7: Serving Data
Part 3: Hands-On Guide to Building a Data Platform
Chapter 8: Hands-On Analytics Engineering
Part 4: DataOps
Chapter 9: Data Quality and Observability
Chapter 10: Writing Code in a Team
Chapter 11: Automating Workflows
Part 5: Data Strategy
Chapter 12: Driving Business Adoption
Chapter 13: Data Governance
Chapter 14: Epilogue
Index
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