User Experience with Big Data

Big data analytics requires new workflows: high latency queries, massively-parallel code, and cloud computing infrastructures all make handling a big dataset different (and harder) than working on a local machine. We are exploring user experiences for analysts, and thinking about new ways to deal with big datasets.

BigDataUX: building a better user experience for Big Data.

Lots of different definitions can be found for "big data," but they all have one aspect in common: big data is inconvenient. It's too big to fit on screen, or in memory, or on disk. There are more fields than are easy to articulate.  And it is so ill-organized and messy that it will take a fair bit of nursing to get it into usable shape.

We want to explore what technologies will make it easier for users -- for data scientists, business intelligence analysts, or anyone with a dataset -- to clean, process, and interact with big datasets. To do that, we've assembled a collaborative team: specialists in UX, visualization and computer-language experts, back-end algorithms and system builders; database designers.

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Andrei Aron
Andrei Aron

Jonathan Goldstein
Jonathan Goldstein

James Terwilliger
James Terwilliger

John Wernsing
John Wernsing