With the advent of whole genome sequencing, large-scale proteomics has rapidly come to dominate the postgenomic age. As such, tandem mass spectrometry has emerged as the most promising and powerful technique in this area but analysis of raw spectra remains one of the principle bottlenecks to making effective use of the technology. Analytical approaches for identifying proteins from MS/MS data fall into two categories: comparing measured fragment spectra to theoretical spectra from sequence databases and de novo peptide sequencing. Available methods still have weaknesses, highlighting the need for new powerful algorithms that are able to exploit the enormous volume of data generated by proteomic experiments. Recent efforts have also been directed towards the identification of post-translational modifications, biomarker discovery and quantitative proteomics. Overall, the intended goal of this review is to give as thorough as possible an overview of state-of-the-art approaches and tools developed to analyze tandem mass spectra in different fields and discuss future directions aimed at overcoming the limits of present methods.