What is the best editing tool to write a thesis, a dissertation or a paper? NOT Word or Pages! It's LaTeX.

In today's video I show you why I decided to use LaTeX to write my data engineering cookbook.

I used it before for my diploma thesis and I am in love again :)

Here's the link to the cheatsheet:

https://wch.github.io/latexsheet/latexsheet.pdf

Check out my Patreon for the Data Engineering Cookbook:

http://bit.ly/PatreonAndreasKretz

Music:

"Day One" by Declan DP

https://soundcloud.com/declandp

Attribution 3.0 Unported

https://creativecommons.org/licenses/by/3.0/

You have certifications or a university degree, but can't find a job?

Sharing your ideas and knowledge will increase your chances!

Here's how you can do that.

Music:

"Day One" by Declan DP

https://soundcloud.com/declandp

Attribution 3.0 Unported

https://creativecommons.org/licenses/by/3.0/

I love agile development. People keep telling you to do Scrum, like it's the only and best choice to be agile. It's not. Here's my take on scrum and my four main beefs with it. Watch out for these issues if you are doing scrum.

So, Cloudera and Hortonworks merge... In today's Plumbers of Data Science Podcast I talk about what these, big data vendors do. How they enable companies, admins and developers to do data science and many more things.

If you are interested in the whole hadoop ecosystem you need to check out this episode. You won't regret it ;)

Is ETL dead in Data Science and Big Data?

In today's podcast I share with you my views on your questions regarding ETL (extract, transform, load).

Data Lakes & Data Warehouse where is the difference?

Is ETL still practiced or did pre processing & cleansing replace it

What would replace ETL in Data Engineering?

How to become a data engineer? (check out my facebook note)

How to get experience training at home?

Real time analytics with RDBMS or HDFS?

What's the difference between Data Scientists & Data Analysts?

What to do to find internships or a full time job?

Data Scientist and Engineer in large and small companies where's the difference? Are Data Engineers generalists or specialists?

Just some questions I go over in this podcast.

You sent me over 100 Questions so, I finally worked up the guts to start with the Q&A videos. Answering your questions one by one.

Turns out it's a lot of fun :)

Without the proper tools and techniques of version control the team's efficiency goes down the drain. In this episode I talk about how tools like Jira enable you to collect bugs, future features or change requests. How they enable you to create and organize versions, add items to a version and assign items to developers. Once this is done, the team can efficiently start coding with the help of source code management systems like GitHub. How does all that work? Check out this episode to find out :)

You need to become comfortable with distributed processing. Data Science or the Internet of Things, the amount of data that is getting produced and processed grows like crazy. In this podcast I talk about how a platform for distributed processing looks like.

I talk about the different layers that need parallelization, as well as the tools you can use for on premise installations or clouds like AWS, Azure or Google Cloud. Big Data tools like Kafka, Spark or server less like Kinesis or Lambda functions.

For me, school and university was hard. The lectures, sitting down and getting told how things work.

Reading books and learning dry stuff was a drag. I was never good at writing tests.

Some people excel at this. I was often envious.

Over the years I found out what my problem is. I learn differently.

I am a learning by doing guy. What does that means and how am I dealing with it?

Check out this episode.

Maybe you have the same problem.