Open data analysis platforms are being adopted to support collaboration in science and
business. Studies suggest that analytic work in an enterprise occurs in a complex ecosystem …

Frameworks for big data arguably began with Google's use of MapReduce. Since then, a
huge amount of progress has been made in the development of big data frameworks, many …

This paper presents the results of an ethnographic study focused on how data science
projects were conducted within a global media advertising company. Observations, via …

Effective data visualization is a key part of the discovery process in the era of “big data”. It is
the bridge between the quantitative content of the data and human intuition, and thus an …

Big data analytic (BDA) systems leverage data distribution and parallel processing across a
cluster of resources. This introduces a number of new challenges specifically for analytics …

We present a vision of a technology and domain agnostic service that will store metadata
that describes properties of the diverse data sets in an enterprise (or across several …

Consider the emerging role of data science teams embedded in larger organizations.
Individual analysts work on loosely related problems, and must share their findings with …

This paper documents the learning objectives, curriculum design, technology infrastructure,
and classroom experience for a" big data mining and analytics" course at a small liberal arts …

In this work we address the growing need for mechanisms for intranode application
composition. We provide a novel shared memory interface that allows composite …

Geospatial data volume exceeds hundreds of Petabytes and is increasing exponentially
mainly driven by images/videos/data generated by mobile devices and high resolution …