I have recently been asked: "What is the difference between BI, Data Science and Big Data". So, it thought I make a quick podcast about this for you guys. I think especially beginners will help this a lot.

Big Data tools are very important. But how deep should you really go as a data scientist?

How do you best learn all this stuff?

Some questions I try to answer in this episode.

Time series data is tricky. Especially if you have missing data.

In this episode I talk about a few things you can do to handle this problem.

A 5 minute rant why the cloud is safe.

Hey Podcast, in this episode I talk about the core functions of Hadoop.

There are three different methods of streamging: At least once, at most once and exactly once. Listen why it makes a huge difference which one you use. Because not every system or tool supports all three.

Where to get dirty data to train cleaning it?

What are unicorn data scientists and what is THE skill you need if you aren't one.

How to define a data science problem.

NoSQL databases like HBase are awesome!

But why and when should you use them?

How does a key value store like HBase work?

Today I am talking about exactly that

Creating a Gaming-AI with Reinforcement Learning • Creating a Gaming-AI with Reinforcement Learning