Storage and recovery of warehouse data in the cloud

• Grant number: 12/13158-9
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: December 01, 2012
• End date: December 01, 2017
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Principal Investigator: Cristina Dutra de Aguiar
• Grantee: Jaqueline Joice Brito
• Host 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

Abstract

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)

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. (12/13158-9, 18/22277-8)

BRITO, JAQUELINE JOICE; MOSQUEIRO, THIAGO; CIFERRI, RICARDO RODRIGUES; DE AGUIAR CIFERRI, CRISTINA DUTRA; ALTINTAS, I; NORMAN, M; DONGARRA, J; KRZHIZHANOVSKAYA, VV; LEES, M; SLOOT, PMA. Faster cloud Star Joins with reduced disk spill and network communication. PROCEEDINGS OF THE XI LATIN AND AMERICAN ALGORITHMS, GRAPHS AND OPTIMIZATION SYMPOSIUM, v. 80, p. 12-pg., 2016-01-01. (12/13158-9)