This report documents the program and the outcomes of Dagstuhl Seminar 17461 "Connecting Visualization and Data Management Research". Seminar November 12-17, 2017-http://www.dagstuhl.de/17461 What prevents analysts from acquiring wisdom from data sources? To use data, to better understand the world and act upon it, we need to understand both the computational and the human-centric aspects of data-intensive work. In this Dagstuhl Seminar, we sought to establish the foundations for the next generation of data management and visualization systems by bringing together these two largely independent communities. While exploratory data analysis (EDA) has been a pillar of data science for decades, maintaining interactivity during EDA has become difficult, as the data size and complexity continue to grow. Modern statistical systems often assume that all data need to fit into memory in order to support interactivity. However, when faced with a large amount of data, few techniques can support EDA fluidly. During this process, interactivity is critical: if each operation takes hours or even minutes to finish, analysts lose track of their thought process. Bad analyses cause bad interpretations, bad actions and bad policies. As data scale and complexity increases, the novel solutions that will ultimately enable interactive, large-scale EDA will have to come from truly interdisciplinary and international work. Today, database systems can store and query massive amounts of data, including methods for distributed, streaming and approximate computation. Data mining techniques provide ways to discover unexpected patterns and to automate and scale well-defined analysis Except where otherwise noted, content of this report is licensed under a Creative Commons BY 3.0 Unported license