I think that's his point. Companies are chasing "big data" because it's a great buzzword without considering whether it's something they actually need or not.
A well-rounded, hype-resistant developer would look at the same problem and say, "wha? Nah, I'll just write a dozen lines of PowerShell and have the answer for you before you can even figure out AWS' terms of use..."
I don't think the article talks about this specifically but there's also a tendency to say "big data" when all you need is "statistically-significant data". If you're Netflix, if you just want to figure out how many users watch westerns for marketing purposes, you don't need to check literally every user, just a large enough sample so that you can get a 95% confidence or so. But I've seen a lot of companies use their "big data" tools to get answers to questions like that, even though it takes longer than just sampling the data in the first place.
(Now Netflix recommendations, that's a big data problem because each user on the platform needs individualized recommendations. But a lot of problems aren't. And it takes that well-rounded hype-resistant guy to know which are and which aren't.)
A well-rounded, hype-resistant developer would look at the same problem and say, "wha? Nah, I'll just write a dozen lines of PowerShell and have the answer for you before you can even figure out AWS' terms of use..."
I don't think the article talks about this specifically but there's also a tendency to say "big data" when all you need is "statistically-significant data". If you're Netflix, if you just want to figure out how many users watch westerns for marketing purposes, you don't need to check literally every user, just a large enough sample so that you can get a 95% confidence or so. But I've seen a lot of companies use their "big data" tools to get answers to questions like that, even though it takes longer than just sampling the data in the first place.
(Now Netflix recommendations, that's a big data problem because each user on the platform needs individualized recommendations. But a lot of problems aren't. And it takes that well-rounded hype-resistant guy to know which are and which aren't.)