Weather scientists have been collection data since the beginning of the century and they are still no better at predicting the weather than they were at the beginning of the century. Economists are in the same boat.
If you're going to disagree with a premise, it might be better to pick counter-examples that are actually, you know, true.
Huh? I'm pretty sure both economists and weather scientists have tons of data but their theories to explain that data have been stagnating for a while now. Economic crashes and booms still happen and nobody knows why even though there is a lot of historical market data people still don't know what leads to them and how to stop them. When was the last time you got an accurate rain forecast? 40% chance of rain? What does that even mean? It either rains or it doesn't and I want to know exactly which and nobody will figure out how to do so anytime soon. While I'm at it I will throw the human genome at you as well. Big pharma was promising untold breakthroughs once we figured out the stuff people are made from but the results have been unspectacular since cancer incidence and whatever other incidence you can think of has been steady and even increasing. The only time big pharmacy companies made any breakthroughs were when they were trying to figure out something and accidentally figured out something else or invented some condition, ADHD anyone? The best treatment even after all the data collection and genome extraction still is prevention and your grandma knew that and she lived during a time when the number 23 counted for big data. So I'm not holding out my breath on any promises made with big data as a powerpoint bullet.
The main problem with all big data sets is that nobody knows how to handle them globally. All algorithms and theories treat the data locally and then try to collate the local pieces to get a global picture. This is fine when your data sets underlying structure is a graph or can be treated as some kind of graph. So the future doesn't belong to data scientists or statisticians but to the people that will figure out how to treat large non-graph like data sets in a meaningful way.
If you're going to disagree with a premise, it might be better to pick counter-examples that are actually, you know, true.