Data Warehousing and Business Intelligence: An Open Source Solution

Author(s):  
Lakshman Bulusu
Author(s):  
Moez Essaidi ◽  
Aomar Osmani

In recent years, the data warehousing infrastructures have undergone many changes in various aspects. This is usually due to many factors: the emergence of Software-as-a-Service (SaaS) architecture model; the success of agile and iterative Data Warehouse (DW) development approaches; the introduction of new approaches based on the Model Driven Architecture (MDA); the changing needs of organizations and the extension of the DW into new application areas; and the evolving of standards and open-source technologies. This chapter explores several aspects that may influence the next-generation of data warehousing platforms: the architectural aspects for business intelligence-as-a-service deployment, the promising open industry standards and technologies recommended for use, and the emerging methodological aspects for DW components engineering.


Author(s):  
Bruno Santos ◽  
Francisco Sério ◽  
Steven Abrantes ◽  
Filipe Sá ◽  
Jorge Loureiro ◽  
...  

Author(s):  
Anne Cleven ◽  
Robert Winter ◽  
Felix Wortmann

Business intelligence (BI) and data warehousing (DWH) research represent two increasingly popular, but still emerging fields in the information systems (IS) academic discipline. As such, they raise two substantial questions: Firstly, “how rigorous, i.e., fundamental, constituent, and explanatory, is DWH BI research?” and, secondly, “how relevant, i.e., useful and purposeful, is this research to practitioners?” In this article, the authors uphold the position that relevance and rigor are by no means dichotomous, but two sides of the same coin. Naturally, this requires well-defined approaches and guidelines—for scholarship in general and DWH/BI research in particular. Therefore, this paper proposes the competence center (CC) approach—a private-public partnership between academia and practice. The authors illustrate how the CC approach can be applied within the field of DWH/BI and suggest that a close link between research and practice supports both enhancing relevance to practice and strengthening rigor of research.


Author(s):  
Jorge Bernardino ◽  
Pedro Caldeira Neves

The importance of supporting decision making for improving business performance is a crucial, yet challenging task in enterprise management. The amount of data in our world has been exploding and Big Data represents a fundamental shift in business decision-making. Analyzing such so-called Big Data is becoming a keystone of competition and the success of organizations depends on fast and well-founded decisions taken by relevant people in their specific area of responsibility. Business Intelligence (BI) is a collection of decision support technologies for enterprises aimed at enabling knowledge workers such as executives, managers, and analysts to make better and faster decisions. We review the concept of BI as an open innovation strategy and address the importance of BI in revolutionizing knowledge towards economics and business sustainability. Using Big Data with Open Source Business Intelligence Systems will generate the biggest opportunities to increase competitiveness and differentiation in organizations. In this chapter, we describe and analyze four popular open source BI systems - Jaspersoft, Jedox, Pentaho and Actuate/BIRT.


2008 ◽  
pp. 379-391 ◽  
Author(s):  
Jörg Becker ◽  
Björn Niehaves ◽  
Felix Müller-Wienbergen ◽  
Martin Matzner

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