I decided to rework the cookbook focusing more on case studies and less on explaining tools.

People keep asking me for a path to become a data engineer and, let's be honest, you will never achieve that with just knowledge of the tools.

Finding out how companies do data engineering on their data science platforms is way more useful.

Over the next weeks we will go over each study on my YouTube channel. The stuff we talk about will then go into the cookbook too.

A Introduction into Hadoop HDFS, YARN and MapReduce. 

Yes, Hadoop is still relevant in 2019 even if you look into serverless tools. 

The Internet of things is a huge deal. There are many platforms available. But, which one is actually good?

Join me on a 50 minute dive into the Siemens Mindsphere online documentation.

 I have to say I was super unimpressed by what I found. 

Many limitations, unclear architecture and no pricing available? 

Not good!

A stream full of mediocre guitar playing and great Q&A about Hadoop. 

I have created a Medium Publication especially for us Plumbers of Data Science who work in Data Engineering and Big Data.

It's called, you guessed it, Plumbers of Data Science.

What is the difference between SQL and NoSQL?

In this episode I show you on the example of HBase how a key/value store works. 

On this podcast I talk about data warehouses and data lakes.

When do people use which? What are the pros and cons of both?

Architecture examples for both and does it make sense to completely move to a data lake?

In this episode I talk about how you can gain a competitive edge on the job market. It's super simple, you can and should start with it TODAY by putting yourself out there. 

The Data Science Hype is still strong. Where's the industry going, towards a cliff? Here's what can you do?

In this episode I show you the first version of my data engineering cookbook.