Data Science and Systems Integration Blog Post

[Ackbach]

Really excited about this blog post by yours truly. Wineman Technology is going places!

 

[Jameson]

Interesting article!

I work with large amounts of data every day and would consider myself an expert in the field when considering the whole continuum of "Can't use a computer" to "Coding at Google". I grab data, clean it, join it, model it, and present it.

That is important to your point, because what I lose in my years of training is the ability to see data and a problem with new eyes. Once you know something, you can try to empathize with the mind of someone who doesn't know it but it is quite difficult. Even worse, you can be very unaware of the facts that you internally assume everyone must know yet they don't.

So I fully agree with you that systems benefit from building bottom-up, not top-down. Some guidance is helpful but too much will leave the end user clueless and frustrated.

 

[Ackbach]

Interesting article!

I work with large amounts of data every day and would consider myself an expert in the field when considering the whole continuum of "Can't use a computer" to "Coding at Google". I grab data, clean it, join it, model it, and present it.

That is important to your point, because what I lose in my years of training is the ability to see data and a problem with new eyes. Once you know something, you can try to empathize with the mind of someone who doesn't know it but it is quite difficult.

Yeah, yeah. Total nerd. I get it. ;)

Even worse, you can be very unaware of the facts that you internally assume everyone must know yet they don't.

So I fully agree with you that systems benefit from building bottom-up, not top-down.

I'm a hair puzzled. I thought I was advocating for a top-down design approach, which is simply what a typical statistics textbook will tell you. If you have an hypothesis at hand (big question, in the parlance of my blog post), then you can design the system that generates the data that, once analyzed, answers the hypothesis or question. Isn't that a top-down design approach? It is considered "cheating", is it not, to use the same data to generate an hypothesis as well as to test it?

Some guidance is helpful but too much will leave the end user clueless and frustrated.

I'm very curious what you mean here. Are you talking about achieving that difficult-to-achieve balance in documentation between conciseness and adequacy?

Cheers!

By the way, I LOVE THE QUOTE-BREAKER!