From the linked piece:
In hindsight, his remark was a clear sign that the marketing hype around "big data" had peaked.
This is true, and it provides the context missing from TFS: "Big Data" is over as a marketing term. But as technological term and as far as actual implementation, it is the status quo and forevermore will be.
From a technological perspective, "Big Data" has a simple definition: more data than can be stored on a single machine. And this need will only grow as hard drives and maybe even SSDs plateau while of course enterprise data only grows.
Indeed, TFA itself states (that TFS omitted):
A particularly hot sector has matured around Hadoop, an open-source analytics software platform. Many tech companies are writing software to make Hadoop industrial strength and integrate it with new and existing types of databases.
So, from TFA itself: Hadoop is hot, but the term "Big Data" is not.
Much that is taught in CS today I had to learn on my own because it hadn't matured enough yet to be incorporated into CS programs: multi-threading, unit testing, OOP, SQL, data mining, all of the web technologies, etc.
But perhaps today's graduates will be complaining ten years hence how new graduates just rely on quantum computing searches and don't know anything about pruning search trees.
Seriously, though, to the point, I'd be more leery of those who graduated ten years ago and had not kept up their skills as opposed to those who graduated recently and did not learn skills from ten years ago.
Should be no surprise to anyone who's every played a videogame: he's in "flow" mode.
Which raises the question: how is this news for nerds?
Yes, it is true coders have little time to code. But the author misses the primary cause: the ratio of library/framework code to self-written code.
In the old days (say, 25+ years ago), you would pick up a book -- a single book -- of the OS API calls, memorize, and start coding. Today, with github, it's as if everyone in the world were working on the same single project. Today, a developer needs to learn all these libraries that are coming out daily and how to work with them. In the old days, there was a lot of reinvention and co-invention of the wheel. Today, that is not allowed, because one has an obligation to "buy" (for free) instead of build because of a) of course, development time and b) more importantly, one gets updates/upgrades "for free" without having to invest (much) additional development time, and c) one's organization can advertise in the future for developers who already have experience with that particular library/framework.
To address specifically the reasons identified by the author:
- Deployment. This is big, perhaps even as big as the above. In the old days, deployment was copying a single executable file. Today, not only is deployment to various and numerous servers more complicated, but for the past 20 years we've had people dedicated to managing those servers, called sys admins, to handle all those non-coding tasks. Of course, coders end up doing some admin and admins end up doing some coding, so now for the past couple of years we have a new half-breed, the Dev Ops. The very existence of both sysadmin and dev ops are themselves acknowledgement that coding is a smaller percentage of the total work involved.
- Tools. The author spends most of the piece harping on this, and it's just totally bogus. We've always had source code control, editors, compilers, and linkers, and they've always been a pain at times to work with. But in fact, it's better now because you can find or ask about work-arounds and solutions on StackOverflow instead of calling up tech support at a closed-source vendor.
But this new development paradigm of the global github hive -- where we're all essentially working on and contributing to this one massive codebase that we all have to understand -- is what the author missed. The amount of custom code to actually code is small now, and the majority of time is spent figuring out how to get the various libraries and frameworks to work.
I tell people I will change jobs for a 30% increase in compensation. That results in a job change every seven years, and here's why. There is a difference between the reported and actual rates of inflation. And annual increases at an existing job more closely track reported inflation, whereas job offers from other companies more closely track actual inflation.
For example, if reported inflation is 3% and actual inflation is 7%, then after 7 years that's a 32% difference.