@inbook{2d3ea6d9e55b46d4a6cf48f254ed0160,
title = "A framework for describing big data projects",
abstract = "With the ability to collect, store and analyze an ever-growing diversity of data generated with ever-increasing frequency, Big Data is a rapidly growing field. While tremendous strides have been made in the algorithms and technologies that are used to perform the analytics, much less has been done to determine how the team should work together to do a Big Data project. Our research reports on a set of case studies, where researchers were embedded within Big Data teams. Since project methodologies will likely depend on the attributes of a Big Data effort, we focus our analysis on defining a framework to describe a Big Data project. We then use this framework to describe the organizations we studied and some of the socio-technical challenges linked to these newly defined project characteristics.",
keywords = "Big data, Data science, Process methodology, Project management",
author = "Jeffrey Saltz and Ivan Shamshurin and Colin Connors",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.",
year = "2017",
month = jan,
day = "1",
doi = "10.1007/978-3-319-52464-1_17",
language = "English (US)",
series = "Lecture Notes in Business Information Processing",
publisher = "Springer Verlag",
pages = "183--195",
booktitle = "Lecture Notes in Business Information Processing",
}