Convolutional neural networks for non image dataset
Short answer:

Yes, absolutely

Longer answer:

As a rule-of-thumb, you can always use any technique on any problem, as long as you define it properly. CNNs are meant to work on signal data. 1D signals can be sound waves, financial records, etc. 2D signals are usually images. 3D signals can be videos (with time being the 3rd dimension). And obviously, you can have as many dimensions as you'd like.

So as long as you can turn your input data (let's say a single training instance) into a signal, then be my guest. However, I fail to see how this dataset can be viewed as a signal.