I think there is a huge risk that the data being collected just isn't meaningful to the problem being asked.
For example, if you are trying to predict the weather you'd really like information on how big clouds are moving but all you have is wind speed and humidity.
Everyone acts like having fancier machine learning methods will solve their problem, but often the data just isn't good enough and getting better data is impossible.
For example, if you are trying to predict the weather you'd really like information on how big clouds are moving but all you have is wind speed and humidity.
Everyone acts like having fancier machine learning methods will solve their problem, but often the data just isn't good enough and getting better data is impossible.