Data analysis is a complex process with frequent shifts among data formats and models, and among textual and graphical media. We are investigating how to better support the life cycle of analysis by identifying critical bottlenecks and developing new methods at the intersection of visualization, machine learning, and computer systems. Can we empower users to transform and clean data without programming? Can we design scalable representations and systems to visualize and query big data in real time? How might we enable domain experts to guide machine learning methods to produce effective models? This talk will present selected projects that attempt to address these challenges and introduce new tools for interactive visual analysis.