11 Questions about Data Engineers
What’s the Profession about and where it’s heading?
This is the thirty-fifth edition of CrunchX and here are the stories and resources we thought were worth spending time on.
1. Agile Is Not a Method, Let Alone “The” Method
Since we all love movies, this story compares agile with another method, i.e. The Method. The different vision calls for a different character and a different method. The context determines and refines how we should define working software, and how we should work on it. Not agile. Written by Jasper Sprengers on DZone and editorial selection by Miloš Živković. Read the article here:
2. Write Better Commits, Build Better Projects
To best convey your story, commits should minimize the effort needed to build a mental model of the changes they introduce. More on other tips to craft good commits in the linked story. Written by Victoria Dye on GitHub Blog and editorial selection by Miloš Živković. Read the article here:
3. UML: My Part in its Downfall
I’ve been in the unfortunate position of having to use UML several times and have never seen any benefits to what I’ve also thought was an over-engineered, steep learning curve methodology that, frankly you never need all of. Laurence Tratt’s excellent article “UML: My Part in its Downfall” gives an insightful and detailed retrospective on its origins, aims, and ultimately the reasons for its inevitable downfall. Very much worth a read if you’ve been in the industry, as I have, for some time. Written and published by Laurence Tratt and editorial selection by Dr. Stuart Woolley. Read the article here:
4. AWS Lambda: Trap or Treasure for API Backends?
AWS Lambda is becoming increasingly popular in the software engineering world — paying for processing tasks rather than machines — but is it really worth it? I’ve found it hard to find a conclusive use case myself, Jason Porritt gives an insightful overview in his article “AWS Lambda — Trap or Treasure for API Backends?”. That’s not even to mention cloud lock-in and how an organization can become dependent upon a specific vendor. Written by Jason Porritt on Atomic Object and editorial selection by Dr. Stuart Woolley. Read the article here:
5. 3 Ways to enhance Productivity with AI
Data Scientists have to work with vast amounts of data. In order to get a full overview of everything and analyze these amounts accordingly, this article suggests three different approaches and techniques that include AI. Written and published by ODSC Community and editorial selection by Christianlauer. Read the article here:
6. How to choose a Cloud Machine Learning Platform
This article is concerned with the characteristics that a cloud machine learning platform should have in order to analyze and visualize vast amounts of data in a correct manner and help to complete the machine learning lifecycle. Written by Martin Heller on InfoWorld and editorial selection by Christianlauer. Read the article here:
7. 11 Questions about Data Engineers: What’s the Profession about and where it’s heading?
In this article, a data scientist answers the most common question regarding the tasks, skills, and knowledge that come with this profession. Written by Ilya Moshkov on KDNuggets and editorial selection by Christianlauer. Read the article here:
8. What makes a Visualisation good?
Jeff Heer, a co-collaborator on data visualization tools talks about what one has to do in order to create high-quality data visualizations. Written and published on KDNuggets and editorial selection by Christianlauer. Read the article here:
9. Tesla CEO Elon Musk unveils prototype humanoid Optimus robot
According to Musk, this prototype can do more than what was shown live, but “the first time it operated without a tether was tonight on stage.” Musk predicted it could hit a price of “probably less than $20,000” and later, in a Q&A session, explained that Tesla is very good at building the AI and the actuators necessary for robotics based on the experience of producing drive units for electric cars. Written by Andrew J. Hawkins on The Verge and editorial selection by Aniket. Read the article here:
10. Stadia’s shutdown shocked developers, too
Stadia’s sudden shutdown could have a big impact on developers. The platform never reached critical mass, so developers probably didn’t earn too much by offering their games there. But they likely counted on it as one of many places where people could play their titles. And because Google has already shut off commerce in the Stadia store, developers can’t make money from selling their games during the last months of the service’s life. Written by Jay Peters on The Verge and editorial selection by Aniket. Read the article here:
These are our picks for this week. Hope you found something new, inspiring, astonishing, and knowledgeable news going around the tech space. Thank you very much for taking the time to read this edition of CrunchX. Look out for the next edition the following week.