In a recent review on childhood asthma, we proposed that knowledge gaps will only be addressed by integrating technological advances and human knowledge across diverse disciplines, with a patient at its center (1). So, how far have we come in turning “big data” into actionable information to address some of the most important questions in asthma today, including clinical and mechanistic insights about the architecture of asthma heterogeneity, to inform personalized treatments? In this Update focusing on publications in the American Thoracic Society journals, we review the progress made in 2019 on understanding asthma epidemiology and risk factors, mechanisms underpinning different disease subtypes, therapeutic options and prediction of treatment responses, and highlight areas for future research.