Data science been criticised for over 10 years now, sometimes rightfully and sometimes not. As far as the article - imagine that someone pointed out a bunch crappy software practices and poor outcomes, they put the term "software development" in the title and never told you that the criticisms only apply to a subset of all software jobs and teams. You would then think that software development has fallen out of favour too.

As far as I can tell from the outside it looks like it's not necessarily falling out of favor but fragmenting into different or more specialized roles. Maybe someone who knows more can correct me.

Except that dashboard generation is exactly what "data scientists" do.

(In the same way that "DevOps" is just a fancy name for a "sysadmin with some light scripting skills".)

I'm a DS by title. I don't do any dashboards. Some people on the team collaborate on them occasionally but its generally deciding which metrics are tracked along with creating/maintaining them while the actual dashboard design and creation is done by the frontend team.

The thing is that Data department have essentially swallowed the former analytics departments, and many people who have done business intelligence/business analytics now seem to fall into the data science umbrella.

This is part of the reason the term now refers to different things depending on who you talk to or which team they are a part of. Look at job postings, its extremely difficult to understand what the actual job entails these days.

The job title is too broad to generalise in this way. Many data scientists never touch a dashboard at all, for many others it's a very small part of their job.

Regardless of how significant the data science insights are, in the end the way you communicate them is through some sort of dashboard.

No, not always. And "insights" might not even be a part of your job as a data scientist. (I wrote a longer comment about this in the thread, I don't want to repeat it here)

What if you are building a data product? I'm not communicating anything on a lot of the things I'm building, because they are simply components of a larger software program. I haven't touched a dashboard in years.

DevOps is a set of practises that practically involve frequent deployments, fast cycle times, low release overhead, short feedback paths, quick time-to-restore, and so on.

It's an extension of lean manufacturing to software development, where the focus is on continuously pushing tiny packets of functionality to customers (instead of occasionally pushing huge bundles of features), to react quicker to changing demand and mistaken assumptions.

It is in no way "a sysadmin with scripting skills" -- the name for which, is, by the way, just sysadmin. Sysadmins know how to write Perl and shell and Python and have done so since forever.

I know the sales pitch, spare me.

> ...the name for which, is, by the way, just sysadmin

No, because some time in the past "IT support" (you know, the guys setting up Windows and Wi-Fi routers in your office) got upgraded in name to "sysadmins", and so the old "sysadmins" who knew Unix and how to code some Perl needed a new, untarnished name. Hence, "DevOps".

I once was in a "DevOps" role with the responsibility of getting devs' "works on my machine" code to build in CI.

Fun times trying to get code you didn't write to compile without knowing any context.

Anyways, that sort of turned me off trying to move into programming and so I went back to mechanical engineering after less than a year. Maybe I should have stuck it out longer.

You were on the DevOps team! They did what ops did!

Data science is the transformation of a set of data resources into a representation of a domain of activity that has integrity and utility. The curation, cleaning, integration & analysis of data to create pictures of what is going on won't go out of favour until there are no more pictures of this sort to be made!