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Fundamentals of Analytics Engineering
Fundamentals of Analytics Engineering

Fundamentals of Analytics Engineering: An introduction to building end-to-end analytics solutions

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Profile Icon Dumky De Wilde Profile Icon Taís Laurindo Pereira Profile Icon Ricardo Angel Granados Lopez Profile Icon Lasse Benninga Profile Icon Juan Manuel Perafan Profile Icon Gligorevic Profile Icon Kassapian +3 more Show less
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Full star icon Full star icon Full star icon Full star icon Half star icon 4.7 (3 Ratings)
Paperback Mar 2024 332 pages 1st Edition
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Profile Icon Dumky De Wilde Profile Icon Taís Laurindo Pereira Profile Icon Ricardo Angel Granados Lopez Profile Icon Lasse Benninga Profile Icon Juan Manuel Perafan Profile Icon Gligorevic Profile Icon Kassapian +3 more Show less
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Full star icon Full star icon Full star icon Full star icon Half star icon 4.7 (3 Ratings)
Paperback Mar 2024 332 pages 1st Edition
eBook
₱1284.99 ₱1836.99
Paperback
₱2296.99
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Free Trial
eBook
₱1284.99 ₱1836.99
Paperback
₱2296.99
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Fundamentals of Analytics Engineering

Part 1:Introduction to Analytics Engineering

The first two chapters present the fundamental ideas supporting analytics engineering and the Modern Data Stack. They highlight how analytics engineers utilize software engineering principles to structure, modify, verify, implement, and document data in a reusable manner, ultimately streamlining team effort and time. Conversely, the Modern Data Stack prioritizes rapid delivery, cost-efficiency, and data accessibility, yet it can result in multiple tools and fragmented data.

This section has the following chapters:

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Key benefits

  • Discover how analytics engineering aligns with your organization's data strategy
  • Access insights shared by a team of seven industry experts
  • Tackle common analytics engineering problems faced by modern businesses
  • Purchase of the print or Kindle book includes a free PDF eBook

Description

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.

Who is this book for?

This book is for data engineers and data analysts considering pivoting their careers into analytics engineering. Analytics engineers who want to upskill and search for gaps in their knowledge will also find this book helpful, as will other data professionals who want to understand the value of analytics engineering in their organization's journey toward data maturity. To get the most out of this book, you should have a basic understanding of data analysis and engineering concepts such as data cleaning, visualization, ETL and data warehousing.

What you will learn

  • Design and implement data pipelines from ingestion to serving data
  • Explore best practices for data modeling and schema design
  • Scale data processing with cloud based analytics platforms and tools
  • Understand the principles of data quality management and data governance
  • Streamline code base with best practices like collaborative coding, version control, reviews and standards
  • Automate and orchestrate data pipelines
  • Drive business adoption with effective scoping and prioritization of analytics use cases

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Mar 29, 2024
Length: 332 pages
Edition : 1st
Language : English
ISBN-13 : 9781837636457
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Product Details

Publication date : Mar 29, 2024
Length: 332 pages
Edition : 1st
Language : English
ISBN-13 : 9781837636457
Category :
Concepts :
Tools :

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Table of Contents

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

Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.7
(3 Ratings)
5 star 66.7%
4 star 33.3%
3 star 0%
2 star 0%
1 star 0%
jose salinas iii Aug 08, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I recently finished reading "Fundamentals of Analytics Engineering: An Introduction to Building End-to-End Analytics Solutions," and it has significantly enhanced my understanding of the analytics engineering lifecycle. It just great book that teaches the back end processes with step by step and explains the process.
Amazon Verified review Amazon
Loni Jun 06, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I recently finished reading "Fundamentals of Analytics Engineering: An Introduction to Building End-to-End Analytics Solutions," and it has significantly enhanced my understanding of the analytics engineering lifecycle. This book is a must-read for anyone looking to integrate data analysis and engineering principles effectively. The insights shared by the seven industry experts are both practical and enlightening, covering everything from data ingestion to modeling and visualization. I particularly appreciated the hands-on guidance for building a data platform using tools like Airbyte, DuckDB, dbt, and Tableau. The emphasis on data quality, governance, and collaborative coding practices makes this book an invaluable resource for ensuring data integrity and driving business success. Whether you're a data engineer, analyst, or an aspiring analytics engineer, this book provides the essential techniques and best practices needed to develop scalable, end-to-end analytics solutions. Highly recommended!
Amazon Verified review Amazon
Johnny Winter Aug 29, 2024
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
My only real complaint about this book is that the title doesn't do justice to the breadth of information contained in it.Whilst this may be aimed at fledgling Analytics Engineers it really covers the fundamentals of the entire Modern Data Stack.I think this is a great read for anyone starting out in data and gives a great overview of the evolution of data architectures as well as the essential concepts for all layers of modern day implementations.
Amazon Verified review Amazon
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