Caravan: Provisioning for what-if analysis

Problems of what-if analysis (such as hypothetical deletions, insertions, and modifications) over complex analysis queries are increasingly commonplace, e.g., in forming a business strategy or looking for causal relationships in science. Here, data analysts are typically interested only in task-specific views of the data, and they expect to be able to interactively manipulate the data in a natural and seamless way — possibly on a phone or tablet, and possibly via a spreadsheet or similar interface without having to carry the full machinery of a DBMS. The Caravan system enables what-if analysis: fast, lightweight, interactive exploration of alternative answers, within views computed over large-scale distributed data sources. Our novel approach is based on creating dedicated provisioned autonomous representations, or PARs. PARs are compiled out of the data, initial analysis queries and user-specified what-if scenarios. They allow rapid evaluation of what-if scenarios without accessing the original data or performing complex query operations. Importantly, the size of PARs is governed by the parameters of the what-if analysis and is proportional to the size of the initial query answer rather than the typically much larger source data. Consequently, many what-if analysis tasks performed through PAR evaluations can be done autonomously, on limited-resource devices. We describe our model and architecture, demonstrate preliminary performance results, and present several open implementation and optimization issues.