research-article

Big Data Technologies to Improve Medical Data Warehousing

Authors:

Abderrazak Sebaa,

Abdelkamel TariAuthors Info & Claims

BDCA'17: Proceedings of the 2nd international Conference on Big Data, Cloud and Applications

Article No.: 21, Pages 1 - 5

https://doi.org/10.1145/3090354.3090376

Published: 29 March 2017 Publication History

Abstract

The purpose of this review is to explore how the use of big data technology improves the performance of medical data warehousing. Indeed, traditional data warehousing tools can no longer be used to handle the volume, variety, and velocity of today's data-centric medical applications. Moreover, Big data technologies can be used to process the streams of medical data, they increase performance by using a cluster of existing networked nodes through powerful processing of these streams. In this paper, we provide an overview of state-of-the-art research issues of data warehousing technologies in the medical field and the opportunities presented by big data technologies. Whereas, an appropriate use of the current technology of big data especially Hadoop could help to overcome issues of medical data warehousing.

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Cited By

Volk MStaegemann DProthmann FTurowski K(2020)Towards an Automatized Way for Modeling Big Data System ArchitecturesBusiness Information Systems10.1007/978-3-030-53337-3_4(46-60)Online publication date: 22-Jul-2020
https://doi.org/10.1007/978-3-030-53337-3_4
Sebaa AChikh FNouicer ATari A(2018)Medical Big Data WarehouseJournal of Medical Systems10.1007/s10916-018-0894-942:4(1-16)Online publication date: 1-Apr-2018
https://dl.acm.org/doi/10.1007/s10916-018-0894-9

Index Terms

Big Data Technologies to Improve Medical Data Warehousing
1. Information systems
  1. Data management systems
    1. Information integration
      1. Data warehouses

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Published In

cover image ACM Other conferences

BDCA'17: Proceedings of the 2nd international Conference on Big Data, Cloud and Applications

March 2017

685 pages

ISBN:9781450348522

DOI:10.1145/3090354

Conference Chairs:
Mohamed Lazaar
ENSA, Tetuan, Morocco
,
Youness Tabii
ENSA, Tetuan, Morocco
,
Mohamed Chrayah
ENSA, Tetuan - Morocco
,
Mohammed Al Achhab
ENSA, Tetuan, Morocco

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Ministère de I'enseignement supérieur: Ministère de I'enseignement supérieur

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 29 March 2017

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BDCA'17

BDCA'17: 2nd international Conference on Big Data, Cloud and Applications

March 29 - 30, 2017

Tetouan, Morocco

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Cited By

Volk MStaegemann DProthmann FTurowski K(2020)Towards an Automatized Way for Modeling Big Data System ArchitecturesBusiness Information Systems10.1007/978-3-030-53337-3_4(46-60)Online publication date: 22-Jul-2020
https://doi.org/10.1007/978-3-030-53337-3_4
Sebaa AChikh FNouicer ATari A(2018)Medical Big Data WarehouseJournal of Medical Systems10.1007/s10916-018-0894-942:4(1-16)Online publication date: 1-Apr-2018
https://dl.acm.org/doi/10.1007/s10916-018-0894-9

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