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Storage and recovery of warehouse data in the cloud

Grant number: 12/13158-9
Support type:Scholarships in Brazil - Doctorate
Effective date (Start): December 01, 2012
Effective date (End): December 01, 2017
Field of knowledge:Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
Principal researcher:Cristina Dutra de Aguiar Ciferri
Grantee:Jaqueline Joice Brito
Home Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
Associated scholarship(s):15/11106-0 - A model-based OLAP approach, BE.EP.DR


In recent years, research related to data warehousing and OLAP (online analytical processing) has been the focus of interest from both academia and industry, producing several important technologies for the design, management and use of information systems for decision support. These technologies are mostly aimed to environments that we call conventional, which do not provide a cloud-computing framework. However, a cloud data warehouse introduces several advantages to conventional data warehousing applications, as described as follows. It supports the storage of increasing data warehouse volumes and the execution of OLAP queries over these voluminous data. It also decreases the costs related to hardware and maintenance. Furthermore, it guarantees flexibility to the decision-making services offered. Despite these advantages, the research on cloud data warehouses is in its initial stage and, therefore, there are several research opportunities that have not been addressed yet. These opportunities motivate the development of this PhD project, which focuses on the storage and recovery of warehouse data in the cloud, considering two main aspects: (i) How to store and organize warehouse data in the cloud.; and (ii) How to efficiently process OLAP queries in the cloud. Therefore, this PhD project aims to investigate a gap in the literature of cloud data warehouses, as it investigates this innovative and challenge research topic. (AU)

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Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
BRITO, JAQUELINE J.; MOSQUEIRO, THIAGO; CIFERRI, RICARDO R.; CIFERRI, CRISTINA D. A. Random access with a distributed Bitmap Join Index for Star Joins. HELIYON, v. 6, n. 2 FEB 2020. Web of Science Citations: 0.
Academic Publications
(References retrieved automatically from State of São Paulo Research Institutions)
BRITO, Jaqueline Joice. Data Warehouses na era do Big Data: processamento eficiente de Junções Estrela no Hadoop. 2017. Doctoral Thesis - Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação São Carlos.

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