Recommended Books And Courses#


About Books and Courses#

This is a collection of books and courses I can recommend personally. They are great for every data engineering learner.

I either have used or own these books during my professional work.

I also looked into every online course personally.

If you want to buy a book or course and support my work, please use one of my links below. They are all affiliate marketing links that help me fund this passion.

Of course all this comes at no additional expense to you, but it helps me a lot.

You can find even more interesting books and my whole podcast equipment on my Amazon store:

Go to the Amazon store

PS: Don't just get a book and expect to learn everything

  • Course certificates alone help you nothing
  • Have a purpose in mind, like a small project
  • Great for use at work




Learning Java: A Bestselling Hands-On Java Tutorial


Learning Python, 5th Edition


Programming Scala: Scalability = Functional Programming + Objects


Learning Swift: Building Apps for macOS, iOS, and Beyond

Data Science Tools#

Apache Spark#

Learning Spark: Lightning-Fast Big Data Analysis

Apache Kafka#

Kafka Streams in Action: Real-time apps and microservices with the Kafka Streams API

Apache Hadoop#

Hadoop: The Definitive Guide: Storage and Analysis at Internet Scale

Apache HBase#

HBase: The Definitive Guide: Random Access to Your Planet-Size Data


The Lean Startup#

The Lean Startup: How Today's Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses

Zero to One#

Zero to One: Notes on Startups, or How to Build the Future

The Innovators Dilemma#

The Innovator's Dilemma: When New Technologies Cause Great Firms to Fail (Management of Innovation and Change)

Crossing the Chasm#

Crossing the Chasm, 3rd Edition (Collins Business Essentials)

Crush It!#

Crush It!: Why Now Is The Time To Cash In On Your Passion

Community Recommendations#

Designing Data-Intensive Applications#

"In my opinion, the knowledge contained in this book differentiates a data engineer from a software engineer or a developer. The book strikes a good balance between breadth and depth of discussion on data engineering topics, as well as the tradeoffs we must make due to working with massive amounts of data." -- David Lee on LinkedIn

Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems

Online Courses#

Computer Networking#

The Bits and Bytes of Computer Networking (Coursera)

Spring Framework#

Building Cloud Services with the Java Spring Framework (Coursera)

Machine Learning Stanford#

Machine Learning (Coursera)

IOS App Development Specialization#

iOS Development for Creative Entrepreneurs Specialization (Coursera)