Neuroimaging datasets are growing increasingly large and complex. With this new reality comes the need for principled statistical methods and thinking to analyze the resulting data and identify meaningful effects. Some commonly used statistical methods will carry over to this new paradigm, while others will need refinement. In this talk we will seek to highlight some of the opportunities and challenges that lay ahead. We will also touch upon issues related to reproducibility, reliability, and causality, as well as the importance of evaluating results across different settings.