Authors:
Pedro Joel Ferreira
1
;
Ana Almeida
1
and
Jorge Bernardino
2
Affiliations:
1
Instituto Superior de Engenharia do Porto, Portugal
;
2
Instituto Superior de Engenharia de Coimbra, Portugal
Keyword(s):
Cloud Computing, Data Warehousing, Cloud Data Warehousing.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Business Analytics
;
Business Intelligence Applications
;
Data Analytics
;
Data Engineering
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Symbolic Systems
Abstract:
A data warehouse enables the analysis of large amounts of information that typically comes from the
organization's transactional systems (OLTP). However, today's data warehouse systems do not have the
capacity to handle the massive amount of data that is currently produced, then comes the concept of cloud
computing. Cloud computing is a model that enables ubiquitous and on-demand access to a set of shared or
non-shared computing resources (such as networks, servers, or storage) that can be quickly provisioned or
released only with a simple request and without human intervention. In this model, the features are almost
unlimited and in working together they bring a very high computing power that can and should be used for
the most varied purposes. From the combination of both these concepts, emerges the cloud data warehouse.
It advances the way traditional data warehouse systems are defined by allowing their sources to be located
anywhere as long as it is accessible through th
e Internet, also taking advantage of the great computational
power of an infrastructure in the cloud. In this paper, we study two of the most popular cloud data
warehousing market solutions: Amazon Redshift and Microsoft Azure SQL Data Warehouse.
(More)