When IDA began, data sets were small and clean, data provenance and management were not significant issues, workflows and grid computing and cloud computing didn't exist, and the world was not populated with billions of cellphone and computer users. The original conception of intelligent data analysis - automating some of the reasoning of skilled data analysts - has not been updated to account for the dramatic changes in what skilled data analysis means, today. IDA might update its mission to address pressing problems in areas such as climate change, habitat loss, education, and medicine. It might anticipate data analysis opportunities five to ten years out, such as customizing educational trajectories to individual students, and personalizing medical protocols. Such developments will elevate the conference and our community by shifting our focus from arbitrary measures of the performance of isolated algorithms to the practical, societal value of intelligent data analysis systems.