The biggest shift has been towards data lake (store everything) away from data cubes (store aggregates). This makes it orders of magnitude easier to diagnose, debug, and assert the correctness of data.
So these trends aren’t in a vacuum, they directly support the issues you discuss.
> Most of the projects I've seen or heard of are just people taking the same old data ...
I don’t disagree with you here. But in my experience it’s about getting Frank in marketing to use the same numbers as everyone else.
When you have 5 different ads platforms that all take revenue credit for a single conversion and have conflicting attribution models, and none of them add up to what accounting says is in the bank account. That’s a hairy problem.
There are different flavors of that class of problem at lots of companies.
So these trends aren’t in a vacuum, they directly support the issues you discuss.
> Most of the projects I've seen or heard of are just people taking the same old data ...
I don’t disagree with you here. But in my experience it’s about getting Frank in marketing to use the same numbers as everyone else.
When you have 5 different ads platforms that all take revenue credit for a single conversion and have conflicting attribution models, and none of them add up to what accounting says is in the bank account. That’s a hairy problem.
There are different flavors of that class of problem at lots of companies.