Two methods for fast analysis of Collective Thomson Scattering (CTS) spectra are presented: Function Parametrization (FP) and feedforward Artificial Neural Networks (ANNs). At this time, a CTS diagnostic is being commissioned at the Wendelstein 7-X (W7-X) stellarator, with ion temperature measurements in the plasma core as its primary goal. A mapping was made from a database of simulated CTS spectra to the corresponding ion and electron temperatures (Ti and Te). The mean absolute mapping errors are 4.2% and 9.9% relative to the corresponding Ti, for the ANN and FP, respectively, for spectra with Gaussian noise equivalent to 10% of the average of the spectral maxima in the database at 650 sampling points per GHz and within a limited parameter space. Although FP provides some insight into the information contents of the CTS spectra, ANNs provide a higher accuracy and noise robustness, are easier to implement, and are more adaptable to a larger parameter space. These properties make ANN mappings a promising all-round method for fast CTS data analysis. Addition of impurity concentrations to the current parameter space will enable fast bulk ion temperature measurements in the plasma core region of W7-X.