Influenza A virus (IAV) is an endemic respiratory pathogen of commercial swine that causes coughing, labored breathing, lethargy, and inappetence. IAV is a particularly frustrating pathogen to control due to its vast potential for rapid increases in genetic and antigenic diversity. Control methods, namely well-matched vaccines, are hindered by this complicated landscape. The objective of the studies within this dissertation was to utilize existing surveillance data to further characterize IAV evolution at both a national and farm level, as well as suggest improvements to surveillance efforts that can increase the usability of the data in the future. The first step in addressing this objective was the application of a near-real-time phylogenetic visualization tool, Nextstrain, to IAV in swine. We used a clade that was increasing in detection frequency, H3 1990.4.a, as a prototype and demonstrated that phylogenetic visualization has the utility of investigating the shifting frequency of different genetic clades. As a follow-up to this study, we investigated the role of the nucleoprotein (NP) in transmission between pigs and, more generally, internal gene constellations as a critical factor in the success of a HA/NA pairing. Lastly, we described IAV diversity, reassortment, and transmission at the farm level, which is most applicable to swine veterinarians and producers. Each aspect of this dissertation was designed to use computational analyses of IAV surveillance data to enhance our understanding of genetic diversity, clade dynamics, reassortment, and transmission. Each chapter builds on the others by analyzing different levels and types of surveillance (passive, active, whole genome) data and offering unique insights into the virus accordingly. This research shows that informatics methods should continue to be applied to swine disease surveillance data and be used to provide feedback on potential improvements for future surveillance efforts.