Plumbers of Data Science

There is this other data science job called data engineer and it's super important. Because data science does not equal data scientist. In today's podcast I talk about how I finally realized that data engineering is my real passion. Definitely check it out, chances are high that data engineering is your thing too.

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

Loosing money with data science in the short term does not matter. It's about the long run, not quick sales. This is a story about how this happened in the insurance industry. And how to go at it to turn this loss into a win

Swish the Swedish Fintech that Blew My Mind in 2017

Chat and Q&A about data science with data scientists

It is very important for me to keep track of emerging technologies and trends. You want to know where the industry is headed. You don't want to miss the next big thing. This is where Gartner's Hype Cycles help a lot. Especially the hype cycle for emerging tech.

How to convince people that machine learning actually works? It's simpler than you think. You have the data. Data doesn't lie!

Unavailable cellphone coverage really pissed me off. You cannot transmit data and do cloud based analytics during that time. That is why edge devices in the field have to get more and more get analytics capabilities built in. For instance in a container ship.

In this episode I talk about the 4 Vs of big data. And how Big Data can save you from catastrophic success.

Doing machine learning in production is very different then for proof of concepts or in education. One of the hardest parts is keeping models updated.

Choose between Big Data & Data Science • Choose between Big Data & Data Science • Choose between Big Data & Data Science

How Data Science Transforms Agriculture | DailyKayy 004 • How Data Science Transforms Agriculture | DailyKayy 004 • How Data Science Transforms Agriculture | DailyKayy 004

Insurance companies use data science to detect fraudulent cases. Saving themselves and the customers money

How Smartwatches and Fitbits Transform Healthcare • How Smartwatches and Fitbits Transform Healthcare

Docker is so awesome for beginners. Preconfigured images let you start coding in minutes. No annoying dev environment setup.

Social media, Product development. Get that data and analyze it! Start winning!