During exploratory data analysis, visualizations are often useful for making sense of complex data sets. However, as data sets increase in size and complexity, static information visualizations decrease in comprehensibility. Interactive techniques can yield valuable discoveries, but current data analysis tools typically support only opportunistic explora- tion that may be inefficient and incomplete. We present a refined architecture that uses systematic yet flexible (SYF) design goals to guide users through complex exploration of data over days, weeks and months. The SYF system aims to support exploratory data analysis with the simplicity of an e-commerce check-out while providing added flexibility to pursue insights. The SYF system pro- vides an overview of the analysis process, suggests unex- plored states, allows users to annotate useful states, supports collaboration, and enables reuse of successful strategies. The affordances of the SYF system are demonstrated by integrating it into a social network analysis tool employed by social scientists and intelligence analysts. The SYF sys- tem is tool-independent and can be incorporated into other data analysis tools using our open-source infrastructure.