Data Data everywhere and not a drop to drink
We are inundated with data haystacks looking for needles, that we are not sure what they are or if they're there.
DDD (Data Directed Descisioning) needs "context" and the greater picture, but more data really does not provide it, it needs wetware (people) on the ground doing interviews making assessments and writing computer understandable reports.
Then there is behavioral economics aspects - the biases, especially "confirmation bias", and while the wetware are prone to this bug, I've not seen the AI industry admit to it in neural networks and machine learning yet. but we have seen hints where self driving vehicles cannot determine if a vehicle is moving when it is traveling at speed or facial recognition can be fooled or distracted.
We are not super-human, nor are our computers super-computer just because they can self teach themselves some narrowly focused game such as Go.
Don't become data fools.