Data Fallacies to Avoid

Hard work alone is not enough

Hard work doesn’t matter much if no one recognizes it. Sad but true.

Roadmap to becoming a data engineer in 2021

Sounds about right! =)

Repetition without real progress

… it becomes bad when you continue learning even when you know enough. Even when you’re capable of jumping right into the project and figure things along the way, you keep delaying it. Beginning something new is uncomfortable, therefore instead you choose to read an article or take a course just so you can tell yourself that you’re working, but in reality, you’re just looping, you’re not making any progress on the project.

Repetition (in learning the same topic) can give a false sense of achievement. Of course I will get better repetition after repetition, but that is diminishing return. It is dangerous to indulge in that warm fuzzy feel-good feeling, while the whole time I am just re-learning the same elementary concepts.

Create more

Most knowledge worth having comes from practice. It comes from doing. It comes from creating. Reading about the trade war with China doesn’t make you smarter—it gives you something to say at dinner parties. It gives you the illusion that you have the vaguest idea what is happening in our enormously complex world.

It makes me think how I should spend my time.

The article is a little one-sided, but the point is clear.

The evolution of trust

A nice game or interactive presentation to learn the Game Theory.

COVID-19 Integrated County View

Back to red again…

How to tell if a wall is load-bearing

Roadmap and ETA

Nice article to highlight what usual goes wrong in software development in a corporate setting.


This tesseract app is pretty amazing, can do a OCR very quick. To install on osx:

brew install tesseract
tesseract -l eng ~/Desktop/ScreenShot.png output

That creates output.txt

The recognized text is not perfect all the times, but good enough.