Top Data Engineering books recommended by experts

At MentorCruise, we are all about making the most out of the experience of others. As part of that, we've connected and asked dozens of experts and professionals about their favourite Data Engineering books – and here are the answers.

Table of Contents

Fundamentals of Data Engineering

Understanding the concepts of Data Engineering starts with understanding the fundamentals. On your way to mastery, it's crucial for you to understand how certain concepts were derived, and why things work like they do. Starting with these resources is the best way to do so.

Spark: The Definitive Guide: Big Data Processing Made Simple

Learn how to use, deploy, and maintain Apache Spark with this comprehensive guide, written by the creators of the open-source cluster-computing framework. With an emphasis on improvements and new features in Spark 2.0, authors Bill Chambers and Matei Zaharia break down Spark topics into distinct sections, each with unique goals.

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Big Data

Big Data teaches you to build big data systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data. It describes a scalable, easy-to-understand approach to big data systems that can be built and run by a small team. Following a realistic example, this book guides readers through the theory of big data…

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Data Pipelines Pocket Reference

Data pipelines are the foundation for success in data analytics. Moving data from numerous diverse sources and transforming it to provide context is the difference between having data and actually gaining value from it. This pocket reference defines data pipelines and explains how they work in today's modern data stack.

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The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling

The first edition of Ralph Kimball's The Data Warehouse Toolkit introduced the industry to dimensional modeling,and now his books are considered the most authoritative guides in this space. This new third edition is a complete library of updated dimensional modeling techniques, the most comprehensive collection ever. It covers new and enhanced star schema dimensional modeling patterns, adds tw…

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Ace the Data Science Interview: 201 Real Interview Questions Asked By FAANG, Tech Startups, & Wall Street

Kevin Huo is currently a Data Scientist at a Hedge Fund, and previously was a Data Scientist at Facebook working on Facebook Groups. He holds a degree in Computer Science from the University of Pennsylvania and a degree in Business from Wharton. In college he interned at Facebook, Bloomberg, and on Wall Street.

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Data Engineering with dbt: A practical guide to building a cloud-based, pragmatic, and dependable data platform with SQL

dbt Cloud helps professional analytics engineers automate the application of powerful and proven patterns to transform data from ingestion to delivery, enabling real DataOps.
This book begins by introducing you to dbt and its role in the data stack, along with how it uses simple SQL to build your data platform, helping you and your team work better together. You'll find out how to leverage …

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Additional Data Engineering Reading

These books are not required for you to learn Data Engineering, but they are highly recommended for you to deepen your knowledge.

Fundamentals of Data Engineering: Plan and Build Robust Data Systems

Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you'll learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available through the framework of the data engineering lifecycle.

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Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking

Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also disc…

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Data Engineering with AWS - Second Edition: Acquire the skills to design and build AWS-based data transformation pipelines like a pro

This book, authored by a seasoned Senior Data Architect with 25 years of experience, aims to help you achieve proficiency in using the AWS ecosystem for data engineering. This revised edition provides updates in every chapter to cover the latest AWS services and features, takes a refreshed look at data governance, and includes a brand-new section on building modern data platforms which covers;…

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Specializations and Deeper Data Engineering Knowledge

You've got your basics in order – time to move on to some advanced and specialized concepts. Data Engineering is evolving every day, these books can help you master it.

Database and Expert Systems Applications

The Database and Expert Systems Application -DEXA - conferences are mainly oriented to establish a state-of-the art forum on Database and Expert System applications. But Practice without Theory has no sense, as Leonardo said five centuries ago. In this Conference we try a comprornise between these two complementary aspects. A total of 5 sessions are application-oriented, ranging from classical…

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Advanced Topics in Database Research

Advanced Topics in Database Research is a series of books on the fields of database, software engineering, and systems analysis and design. They feature the latest research ideas and topics on how to enhance current database systems, improve information storage, refine existing database models, and develop advanced applications.

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This list is curated by MentorCruise and can include Amazon affiliate links. Have any other suggestions? Add here.

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