Zettabytes of data are available to be harvested for competitive business advantage, sound government policies, and new insights in a broad array of applications. Yet, most of this data is inaccessible for users, since current data analysis tools require an army of technical people to find, transform, analyze, and visualize data in order to make it consumable for decision making. In this paper, we present work in progress to lower the barriers for data-driven decision making by introducing a systems approach to scale the user experience, not only in the volume and variety of data, but also in the skills required to harvest that data. We call for a new approach for data-intensive applications that engages the user as an intelligent partner in a social and intelligent conversation with data by automating, guiding, and recommending data, transformations, visualizations, analytics, and suggesting collaboration opportunities within an analytics marketplace, and leverages both metadata and semantic information about the data captured from conversations. © 2013 IEEE.