Medical Big Data Warehouse: Architecture and System Design, a Case Study: Improving Healthcare Resources Distribution.

Abderrazak Sebaa, Fatima Chikh, Amina Nouicer, AbdelKamel Tari
Author Information
  1. Abderrazak Sebaa: LIMED Laboratory, Faculty of Exact Sciences, University of Bejaia, Bejaia, Algeria. balzak.sebaa@gmail.com. ORCID
  2. Fatima Chikh: Department of Computer Science, Faculty of Exact Sciences, University of Bejaia, Bejaia, Algeria.
  3. Amina Nouicer: LIMED Laboratory, Faculty of Exact Sciences, University of Bejaia, Bejaia, Algeria.
  4. AbdelKamel Tari: LIMED Laboratory, Faculty of Exact Sciences, University of Bejaia, Bejaia, Algeria.

Abstract

The huge increases in medical devices and clinical applications which generate enormous data have raised a big issue in managing, processing, and mining this massive amount of data. Indeed, traditional data warehousing frameworks can not be effective when managing the volume, variety, and velocity of current medical applications. As a result, several data warehouses face many issues over medical data and many challenges need to be addressed. New solutions have emerged and Hadoop is one of the best examples, it can be used to process these streams of medical data. However, without an efficient system design and architecture, these performances will not be significant and valuable for medical managers. In this paper, we provide a short review of the literature about research issues of traditional data warehouses and we present some important Hadoop-based data warehouses. In addition, a Hadoop-based architecture and a conceptual data model for designing medical Big Data warehouse are given. In our case study, we provide implementation detail of big data warehouse based on the proposed architecture and data model in the Apache Hadoop platform to ensure an optimal allocation of health resources.

Keywords

References

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Grants

  1. B*00620140066/2015-2018/Higher Education and Scientific Research of Algeria and the University of Bejaia

MeSH Term

Algeria
Decision Support Techniques
Health Resources
Humans
Information Storage and Retrieval
Models, Theoretical

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