In most cases hadoop is total overkill -- developers don't understand how to reduce problems, might have never heard of sampling, good data-structures, know your problem, etc.
For sure, there are valid use scenarios for map reduce/hadoop, etc. but in many cases it's a big waste of money.
And I would disagree that Hadoop is a big waste of money. There isn't anything else really that comes close to its cost effectiveness once you reach a certain data size.
"We don't do big data, we do little data" -- said no dev team ever, since Big Data has appeared.
Loading a 100MB Excel file -- big data. Dumping a few GB to SQLite -- big data. And programmers are now of course "Data Scientists".
Same with services. When microservices became cool, all the other services have disappeared and everyone is doing microservices.