Did you know that 'Data Engineer’ is the fastest growing role in the industry?
Nowadays, most data science wannabes are still focused on landing the coveted role of data scientist. That is understandable: all the hype in the media and the community glorifies the role of a data scientist. But it's the data engineer who emerged as the dark horse.
What is not really surprising, truth? Data science Professionals dedicate close to 60-70% of your time to collect, clean and process data, That's exactly the same as a data engineer!
Tech giants like Netflix, Facebook, Amazon, Uber, etc. are collecting data at an unprecedented rate, and they're hiring data engineers like never before. There has been no better time to get into this field!!
Unfortunately, there is no consistent path designed to become a data engineer. Most data science wannabes haven't even heard of the position; they tend to learn about it at work.
I have put together a list of data engineering books to help you get started with this thriving field and make sure you are familiar with the various terms, skills and other required nuances.
And why are the books?
Many successful people attribute their success to reading books. In fact, the founder and CEO of DataPeaker, Mr. Kunal Jain, read a book every week. There is no substitute for books, is still one of the best resources you would like to get your hands on.
Books are a vital way to absorb data engineering information. Let's start!
1. Andreas Kretz's Data Engineering Cookbook
There is a lot of confusion about how to become a data engineer. I've met many data science wannabes who didn't even know this role existed!!
Here's an e-book by Andreas Kertz that has elaborate case studies, codes, podcasts, interviews, case studies and more. I consider this to be a complete package for anyone to become a data engineer.
And the icing on the cake? This ebook is free!! Yes, you can start using it instantly. Learn it, practice and prepare for your data engineering position now!
Click here to access – The Data Engineering Cookbook
2. DW 2.0 – The architecture for the next generation of data warehousing by the father of data warehousing WH Inmon
This book describes the future of data storage that is technologically possible today, both architecturally and technologically.
I really like how the book is carefully structured and covers most of the topics related to data architecture and its underlying challenges., how you can use the existing system and build a data warehouse around it, and best practices to justify expenses in a very practical way.
This book is designed to:
- Anyone aspiring to become a data engineering professional
- Organizations that want to incorporate this capability into their systems.
- Data architects
- DBA
- System designers and
- Data storage professionals
DW 2.0. it is * Written by him “datastore parent”, Bill Inmon, columnist and newsletter editor for The Bill Inmon Channel on Business Intelligence Network.
This is not to be missed!! This is where you can get a copy: Amazon.com.
3. Agile data warehouse design: collaborative dimensional modeling, from the blackboard to the star schematic of Lawrence Corr
This is a great book. Lawrence Corr provides a comprehensive, step-by-step guide to capturing business intelligence and data warehousing requirements and turning them into high-performance models using a technique called model storm. (model + brainstorming).
What's more, you will find a concept called BEAM, an agile approach to dimensional modeling to improve communication between data warehouse designers and business intelligence stakeholders.
Get this book at Amazon.com
4.
What do you want as a data scientist?
How about getting clean and reliable data? With all the business value captured and well presented in the data, would definitely want accurate and robust data models, high application agility and well-designed models as the end result.
How would you feel if someone granted you these wishes and made your dream of becoming a champion data engineer come true?? Then, Why wait for that ‘someone’ grant your wishes when you can find a way to mark your path and get these wishes granted for yourself simply by reading this book?
Yes, this book is the third edition, is a comprehensive library of up-to-date dimensional modeling techniques, the most complete collection in history. Covers new and improved star schematic dimensional modeling patterns, adds two new chapters on ETL techniques, includes new and expanded business matrices for 12 case studies, and more.
You can get a copy here: Amazon.com
5. Learning Spark de Holden Karau
Today, large volumes of data are generated, a scale we can only imagine. Much data plays a vital role in increasing the complexity of operations and that has led to new developments in the field of data engineering..
This excellent book by Holden Karau offers a valuable reference guide for all graduate students., researchers and scientists interested in exploring the potential of Big Data applications.
Dive into the world of innovations in the way you acquire and massage data, the end goal is to get the best and most classified data for your machine learning model. Spark is the most efficient data processing framework in companies today.
Get a copy today! – Amazon.com
Data engineering is a multidisciplinary field with applications in control, Decision theory and the emerging area of bioinformatics. There are no books on the market that put the subject within the reach of non-experts.
Then, if you are just starting out and need a good book to learn all about data engineering, then spark, A computing framework in clusterA cluster is a set of interconnected companies and organizations that operate in the same sector or geographical area, and that collaborate to improve their competitiveness. These groupings allow for the sharing of resources, Knowledge and technologies, fostering innovation and economic growth. Clusters can span a variety of industries, from technology to agriculture, and are fundamental for regional development and job creation.... that is used to process, query and analyze big data, is the tool you must learn and this is your book to read.
All theory and practical concepts are explained in a user-friendly way and in easy-to-understand language.
Get a copy today at Amazon.com
7. Big Data: Principles and best practices of scalable data systems in real time by Nathan Marz
This book is intended for managers, advisers, consultants, specialists, professionals and anyone interested in data engineering evaluation.
Describes a scalable and easy-to-understand approach to big data systems that a small team can build and run.. Following a realistic example, this book guides readers through big data systems theory, how to implement them in practice and how to implement and operate them once they are built.
Therefore, if you are the CEO / CXO of an organization and you want to introduce the practice of Data Engineering in your organization, you should take this book and access your company's data engineering blueprint.
Grab a copy here – Amazon.com
8.
The concepts in this book revolve around the task of collecting data and extracting useful information from that data.. Five discrete sections covered in this book are:
- Data scalability
- Consistency
- Reliability
- Efficiency and
- Maintainability
Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data..
This is where you can get it: Amazon.com
9. Big Data, Black Book: covers Hadoop 2, MapReduce, Hive, YARN, Pig, R and data visualization
The goal of this book is to create a new generation of versatile Big Data analysts and developers, who are fully familiar with basic and advanced analytical techniques for manipulating and analyzing data.
Therefore, if you want to start learning about data engineering tools, this book is a must read. Comprehensively covers all the tools that help you meddle with data and crafting strategies to gain a competitive advantage.
Get your copy here – Amazon.com
Final notes
Becoming a data engineer is not an easy task. Requires a deep understanding of the tools, processes and techniques to extract the best from structured data / unstructured.
You can outline a data engineering path yourself by reading this comprehensive article.: Do you want to become a data engineer? Here's a full list of resources to get you started.
I hope you liked my collection of Data Engineering books!! I would definitely like to know if there are any books that I would recommend.. Share the names in the comment section below.
