Top Data Engineering books recommended by experts

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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.

The Data Warehouse Toolkit

The Data Warehouse Toolkit

One of the most dramatic new developments in database design, the dimensional data warehouse is a powerful database model that.significantly enhances managers' ability to quickly analyze large, multidimensional data sets. Written by the leading proponent of this revolutionary new approach, this valuable book/CD toolkit outfits you with all the nuts-and-bolts information you need to design, build, manage, and use dimensional data warehouses for virtually any type of business application, as well as software for querying dimensional data warehouses.

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Designing Data-Intensive Applications

Designing Data-Intensive Applications

Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords?

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Big Data

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 systems, how to implement them in practice, and how to deploy and operate them once they're built.

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Data Pipelines Pocket Reference

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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Specializations and Deeper Data Engineering Knowledge

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

Advanced Topics in Database Research

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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Database and Expert Systems Applications

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 applications to more unusual ones in Software Engineering.

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Expertise in enabling, developing and deploying robust end-to-end data pipelines and machine learning models that have real world impact on a regular basis. Over the years, I have had the opportunity to work with and learn from some of the best minds at prestigious organizations like Mercedes-Benz and General Motors. โ€ฆ

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I have more than a decade experience in Software Engineering (and related practices including DevOps) and I have been lucky enough to have worked with a bunch of great minds in the big tech giants. I've got a couple of MAANG companies in my kitty and after attending (and cracking) โ€ฆ

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As Managing Consultant for Data Science and Machine Learning, I develop end-to-end machine learning solutions for my clients and help them get business value with their data.

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