# BatchNormalizationLayer instead of data prep

I've trained a neural net to match nx7x5 matrices to nx1 scalars; the n is a number of elements in a sequence. To get a good match I have to do some data prep; basically do a Rescale on each row of the matrix effectivley scaling the data for each row to a number between 0-1. That improves the match quite a lot; but also is a bit tricky and I wanted to use a neural net layer to do that. I'm think BatchNormalizationLayer should allow me to feed the raw data into the network directly? am I correct? I would also like a way to 'see' how the data looks like coming out of the BatchNormalizationLayer to compare it with the input so I can understand it. Below is the link to a small subset of the data.

trainingdata

Thoughts