Task oriented data exploration with human-in-the-loop. A data center migration use case

Abstract

Data exploration is a task that inherently requires high human interaction. The subject matter expert looks at the data to identify a hypothesis, potential questions, and where to look for answers in the data. Virtually all data exploration scenarios can benefit from a tight human-in-the-loop paradigm, where data can be visualized and reshaped, but also augmented with missing semantic information - that the subject matter expert can supplement in itinere. In this demo we show a novel graph-based data exploration model where the subject matter expert can annotate and maneuver the data to answer specific questions. This demo specifically focuses on the task of migrating data centers, logically and/or physically, where the subject matter expert needs to identify the function of each node - a server, a virtual machine, a printer, etc - in the data center, which is not necessarily directly available in the data and to be able to plan a safe switch-off and relocation of a cluster of nodes. We show how the novel human-in-the-loop data exploration and enrichment paradigm helps designing the data center migration plan.