Will Deep Learning Change How Teams Execute Big Data Projects?

Ivan Shamshurin, Jeffrey Saltz

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

As data continues to be produced in ever increasing quantities, and technologies such as high performance computing continue to be enhanced, the number of big data projects using advanced neural network machine learning, often referred to as deep learning, continues to increase. Unfortunately, while much has been written on the use of deep learning algorithms in terms of generating insightful analysis, much less has been written about the project management process methodologies that could enable teams to more effectively and efficiently »do» big data deep learning projects. Specifically, the rapid growth in the use of deep learning techniques might introduce new challenges with respect to how to execute a big data deep learning project, due to how deep learning models can learn features automatically. For example, feature engineering and model evaluation phases of big data projects might grow in importance, while other areas, such as model selection, might decrease in importance. Hence, this paper discusses the key research questions relating the potential impact of the use of deep learning on how teams should execute big data projects.

Original languageEnglish (US)
Title of host publicationProceedings - 2018 IEEE International Conference on Big Data, Big Data 2018
EditorsYang Song, Bing Liu, Kisung Lee, Naoki Abe, Calton Pu, Mu Qiao, Nesreen Ahmed, Donald Kossmann, Jeffrey Saltz, Jiliang Tang, Jingrui He, Huan Liu, Xiaohua Hu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2813-2817
Number of pages5
ISBN (Electronic)9781538650356
DOIs
StatePublished - Jan 22 2019
Event2018 IEEE International Conference on Big Data, Big Data 2018 - Seattle, United States
Duration: Dec 10 2018Dec 13 2018

Publication series

NameProceedings - 2018 IEEE International Conference on Big Data, Big Data 2018

Conference

Conference2018 IEEE International Conference on Big Data, Big Data 2018
CountryUnited States
CitySeattle
Period12/10/1812/13/18

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Keywords

  • deep learning
  • methodology
  • neural networks

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems

Cite this

Shamshurin, I., & Saltz, J. (2019). Will Deep Learning Change How Teams Execute Big Data Projects? In Y. Song, B. Liu, K. Lee, N. Abe, C. Pu, M. Qiao, N. Ahmed, D. Kossmann, J. Saltz, J. Tang, J. He, H. Liu, & X. Hu (Eds.), Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018 (pp. 2813-2817). [8622337] (Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigData.2018.8622337