READ: Rapid data Exploration, Analysis and Discovery
Udayan Khurana, Srinivasan Parthasarathy, Deepak S. Turaga · 2014
Exploratory data analysis (EDA) is the process of discovering im-portant characteristics of a dataset or finding data-driven insights in the corresponding domain. EDA is a human intensive process involving data management, analytic flow deployment and model creation, and data visualization and interpretation. It involves ex-tensive use of analyst time, effort, and skill in data processing as well as domain expertise. In this paper, we introduce READ, a mixed initiative system for accelerating exploratory data analysis. The key idea behind READ is to decompose the exploration pro-cess into components that can be independently specified and auto-mated. These components can be defined, reused or extended using simple choice points that are expressed using inference rules, plan-ning logic, and reactive user interfaces and visualization. READ uses a formal specification of the analytic process for automated model space enumeration, workflow composition, deployment, and model validation and clustering. READ aims to reduce the time re-quired for exploration and understanding of a dataset from days to minutes. 1.