FFT is generally faster than DFT, making DFT seem redundant in many cases. However, DFT can be advantageous when computational speed is not a concern, particularly for obtaining a small number of Fourier coefficients from a large dataset. Conventional FFT algorithms perform efficiently only when the number of data points can be factorized into small integers, which is less restrictive than earlier FFT methods. Precision differences between DFT and FFT are not expected to be significant, although further investigation could provide more insights. Ultimately, the choice between DFT and FFT may depend on specific application requirements rather than inherent advantages.