scholarly journals A review of genomic data warehousing systems

2013 ◽  
Vol 15 (4) ◽  
pp. 471-483 ◽  
Author(s):  
T. Triplet ◽  
G. Butler
Author(s):  
Oscar Romero ◽  
Alberto Abelló

In the last years, data warehousing systems have gained relevance to support decision making within organizations. The core component of these systems is the data warehouse and nowadays it is widely assumed that the data warehouse design must follow the multidimensional paradigm. Thus, many methods have been presented to support the multidimensional design of the data warehouse.The first methods introduced were requirement-driven but the semantics of the data warehouse (since the data warehouse is the result of homogenizing and integrating relevant data of the organization in a single, detailed view of the organization business) require to also consider the data sources during the design process. Considering the data sources gave rise to several data-driven methods that automate the data warehouse design process, mainly, from relational data sources. Currently, research on multidimensional modeling is still a hot topic and we have two main research lines. On the one hand, new hybrid automatic methods have been introduced proposing to combine data-driven and requirement-driven approaches. These methods focus on automating the whole process and improving the feedback retrieved by each approach to produce better results. On the other hand, some new approaches focus on considering alternative scenarios than relational sources. These methods also consider (semi)-structured data sources, such as ontologies or XML, that have gained relevance in the last years. Thus, they introduce innovative solutions for overcoming the heterogeneity of the data sources. All in all, we discuss the current scenario of multidimensional modeling by carrying out a survey of multidimensional design methods. We present the most relevant methods introduced in the literature and a detailed comparison showing the main features of each approach.


Author(s):  
Roelien Goede

Information systems and in particular data warehouses are very expensive systems to develop. It is therefore not advisable to experiment with ideas too different from current practices. This makes it difficult to apply prescriptive theories in an existing field. From theoretical considerations one might want to develop a data warehouse according to another method such as critical systems thinking methodology. It is however very difficult to persuade data warehouse practitioners to attempt such an experiment. This might be because they would rather adhere to known practices or that they are not sufficiently knowledgeable on critical systems thinking (or any other prescriptive theory) to apply it to such an expensive project. This paper describes a method in which prescriptive theories may be used descriptively to analyse their applicability in a specific field of application. The proposed method is used to understand the practices of the data warehouse discipline from the perspectives of the systems thinking discipline. It is also indicated how this method could be used in other studies where the behaviour of participants is viewed from a point of view of which the detail are unknown to the participants.Keywords: Data warehousing, Systems thinking, Prescriptive theory, Descriptive theory, Interpretative research. Disciplines: Information technology, systems theory, data warehousing, hermeneutics


Author(s):  
Zohra Bellahsene

There are many motivations for investigating the view selection problem. At first, materialized views are increasingly being supported by commercial database systems and are used to speed up query response time. Therefore, the problem of choosing an appropriate set of views to materialize in the database is crucial in order to improve query processing cost. Another application of the view selection issue is selecting views to materialize in data warehousing systems to answer decision support queries. The problem addressed in this paper is similar to that of deciding which views to materialize in data warehousing. However, most existing view selection methods are static. Moreover, none of these methods have considered the problem of de-materializing the already materialized views. Yet it is a very important issue since the size of storage space is usually restricted. This chapter deals with the problem of dynamic view selection and with the pending issue of removing materialized views in order to replace less beneficial views with more beneficial ones. We propose a view selection method for deciding which views to materialize according to statistic metadata. More precisely, we have designed and implemented our view selection method, including a polynomial algorithm, to decide which views to materialize.


2017 ◽  
Vol 7 (3) ◽  
pp. 7 ◽  
Author(s):  
Iain Horton ◽  
Yaxiong Lin ◽  
Gay Reed ◽  
Mathieu Wiepert ◽  
Steven Hart

Author(s):  
Gert Van der Westhuizen ◽  
Brian Dollery ◽  
Bligh Grant

The South African local government sector has undergone changes in the post-apartheid era as policy makers have sought to improve basic services provided to disadvantaged local communities. While scholars have considered various dimensions of the reform program, little effort has been directed at evaluating the effectiveness and efficiency dimensions of the changes in service provision, with some notable exceptions (van der Westhuizen and Dollery, 2009; Krugell, et al., 2010). This article seeks to contribute to this literature by evaluating the efficiency with which municipalities have provided (Reconstruction and Development Program) RDP water, RDP sanitation RDP electricity and RDP refuse removal, using Data Envelopment Analysis techniques (DEA) applied to panel data from 2006/2007 to 2008/2009 for 231 local municipalities and 46 district municipalities.Keywords: Data warehousing, Systems thinking, Prescriptive theory, Descriptive theory, Interpretative research. Disciplines: Information technology, systems theory, data warehousing, hermeneutics


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