The case for interactive data exploration accelerators (IDEAs)

Abstract

Enabling interactive visualization over new datasets at "human speed" is key to democratizing data science and maximizing human productivity. In this work, we first argue why existing analytics infrastructures do not support interactive data exploration and then outline the challenges and opportunities of building a system specifically designed for interactive data exploration. Finally, we present an Interactive Data Exploration Accelerator (IDEA), a new type of system for interactive data exploration that is specifically designed to integrate with existing data management landscapes and allow users to explore their data instantly without expensive data preparation costs.