What pre processing should I use on data to feed into a CNN?
You should normalize your input data for different purposes. As you can read from here, Normalizing data is done for accelerating optimization. If you have features with different scales, it will take too much time for your optimizer function to find optimal points. Suppose you have age feature which can change between 0 to 150 (!) and salary which can be changed from 0 to whatever, like 500,000,000 $. your optimization algorithm used in your ML model will take too much time, if possible, to find appropriate weights for each feature. Moreover, if you don't scale your data, your ML algorithm may take too much care to features with large scales. 

You have not explicitly specified your task, if its classification, you may need to turn the labels into one-hot encoded versions or if possible you may need to use word embeding for adding logical distance to different classes. If your task is a regression one, you may need to normalize your outputs. In regression problems it is customary to normalize the output too, because the scale of output and input features may differ.