Business Intelligence and Service Oriented Architecture – Improving IT Investments

2013 ◽  
Author(s):  
Indira Shantapriyan ◽  
Paul Shantapriyan
Keyword(s):  
Business Intelligence ◽  
Service Oriented Architecture ◽  
It Investments ◽  
Service Oriented

Integrated Supply Chain Intelligence through Collaborative Planning, Analytics and Monitoring

2011 ◽  
pp. 43-92 ◽  
Author(s):  
Nenad Stefanovic ◽  
Dusan Stefanovic ◽  
Bozidar Radenkovic
Keyword(s):  
Supply Chain ◽  
Performance Management ◽  
Business Intelligence ◽  
Service Oriented Architecture ◽  
Collaborative Planning ◽  
Research Trends ◽  
Future Research ◽  
Web Based ◽  
Service Oriented ◽  
Integrated Supply Chain

As supply chains are growing increasingly complex, from linear arrangements to interconnected, multi-echelon, collaborative networks of companies, there is much more information that needs to be stored and analyzed than there was just a few years ago. Today, there are variety of business initiatives and technologies such as joint planning and execution, business intelligence, performance management, data mining and alerting that can be used for more efficient supply chain management. However, organizations still lack methods, processes and tools to successfully design and implement these systems. In this chapter, the authors present the integrated supply chain intelligence (SCI) system that enables collaborative planning and decision making through web-based analytics and process monitoring. The system is process based and utilizes business intelligence and Internet technologies. Multi-layered and service-oriented architecture enables composition of the new breed of SCI applications. They describe main elements and capabilities of the system, its advantages over existing systems and also discuss future research trends and opportunities.

Envisioning the Paradigm of Service Oriented Hydrology Intelligence (SOHI)

2010 ◽  
pp. 172-198
Author(s):  
Pethuru Raj Chelliah
Keyword(s):  
Real Time ◽  
Business Intelligence ◽  
Information Technologies ◽  
Service Oriented Architecture ◽  
Knowledge Engineering ◽  
Reference Architecture ◽  
Data Intensive ◽  
Related Data ◽  
On Demand ◽  
Service Oriented

Hydrology is an increasingly data-intensive discipline and the key contribution of existing and emerging information technologies for the hydrology ecosystem is to smartly transform the water-specific data to information and to knowledge that can be easily picked up and used by various stakeholders and automated decision engines in order to forecast and forewarn the things to unfold. Attaining actionable and realistic insights in real-time dynamically out of both flowing as well as persisting data mountain is the primary goal for the aquatic industry. There are several promising technologies, processes, and products for facilitating this grand yet challenging objective. Business intelligence (BI) is the mainstream IT discipline representing a staggering variety of data transformation and synchronization, information extraction and knowledge engineering techniques. Another paradigm shift is the overwhelming adoption of service oriented architecture (SOA), which is a simplifying mechanism for effectively designing complex and mission-critical enterprise systems. Incidentally there is a cool convergence between the BI and SOA concepts. This is the stimulating foundation for the influential emergence of service oriented business intelligence (SOBI) paradigm, which is aptly recognized as the next-generation BI method. These improvisations deriving out of technological convergence and cluster calmly pervade to the ever-shining water industry too. That is, the bubbling synergy between service orientation and aquatic intelligence empowers the aquatic ecosystem significantly in extracting actionable insights from distributed and diverse data sources in real time through a host of robust and resilient infrastructures and practices. The realisable inputs and information being drawn from water-related data heap contribute enormously in achieving more with less and to guarantee enhanced safety and security for total human society. Especially as the green movement is taking shape across the globe, there is a definite push from different quarters on water and ecology professionals to contribute their mite immensely and immediately in permanently arresting the ecological degradation. In this chapter, we have set the context by incorporating some case studies that detail how SOA has been a tangible enabler of hydroinformatics. Further down, we have proceeded by explaining how SOA-sponsored integration concepts contribute towards integrating different data for creating unified and synchronized views and to put the solid and stimulating base for quickly deriving incisive and decisive insights in the form of hidden patterns, predictions, trends, associations, tips, etc. from the integrated and composite data. This enables real-time planning of appropriate countermeasures, tactics as well as strategies to put the derived in faster activation and actuation modes. Finally the idea is to close this chapter with an overview of how SOA celebrates in establishing adaptive, on-demand and versatile SOHI platforms. SOA is insisted as the chief technique for developing and deploying agile, adaptive, and on-demand hydrology intelligence platforms as a collection of interoperable, reusable, composable, and granular hydrology and technical services. The final section illustrates the reference architecture for the proposed SOHI platform.

scholarly journals Investigating the Impact of System Quality on Service-Oriented Business Intelligence Architecture

SAGE Open ◽  
2018 ◽  
Vol 8 (4) ◽  
pp. 215824401880552 ◽  
Author(s):  
Lee-Kwun Chan ◽  
Phooi-Yee Lau
Keyword(s):  
Business Intelligence ◽  
Service Oriented Architecture ◽  
Least Squares Method ◽  
System Quality ◽  
Quality Factors ◽  
Service Oriented ◽  
Managerial Positions ◽  
The Individual ◽  
Partial Least Squares Method ◽  
The Impact

Despite the recognized value that Business Intelligence (BI) systems bring to organizations, our understanding of the system quality and its impact on service-oriented architecture is limited. This study seeks to examine the impact of system quality on service-oriented BI architecture. Following the theory in the Information System success model, this study assesses the factors that can create impact to the individual and the organization. A total of 60 sample data were collected and analyzed using the partial least squares method. Majority of the respondents are the IT practitioners who hold managerial positions in their respective companies. The results suggest there are two sets of system quality factors. This study contributes to the literature of BI architecture. The managerial findings will be useful for BI stakeholders in the planning, reviewing, and implementing of SOA-based BI architecture.

Envisioning the Paradigm of Service Oriented Hydrology Intelligence (SOHI)

2011 ◽  
pp. 1610-1636
Author(s):  
Pethuru Raj Chelliah
Keyword(s):  
Real Time ◽  
Business Intelligence ◽  
Information Technologies ◽  
Service Oriented Architecture ◽  
Knowledge Engineering ◽  
Reference Architecture ◽  
Data Intensive ◽  
Related Data ◽  
On Demand ◽  
Service Oriented

Hydrology is an increasingly data-intensive discipline and the key contribution of existing and emerging information technologies for the hydrology ecosystem is to smartly transform the water-specific data to information and to knowledge that can be easily picked up and used by various stakeholders and automated decision engines in order to forecast and forewarn the things to unfold. Attaining actionable and realistic insights in real-time dynamically out of both flowing as well as persisting data mountain is the primary goal for the aquatic industry. There are several promising technologies, processes, and products for facilitating this grand yet challenging objective. Business intelligence (BI) is the mainstream IT discipline representing a staggering variety of data transformation and synchronization, information extraction and knowledge engineering techniques. Another paradigm shift is the overwhelming adoption of service oriented architecture (SOA), which is a simplifying mechanism for effectively designing complex and mission-critical enterprise systems. Incidentally there is a cool convergence between the BI and SOA concepts. This is the stimulating foundation for the influential emergence of service oriented business intelligence (SOBI) paradigm, which is aptly recognized as the next-generation BI method. These improvisations deriving out of technological convergence and cluster calmly pervade to the ever-shining water industry too. That is, the bubbling synergy between service orientation and aquatic intelligence empowers the aquatic ecosystem significantly in extracting actionable insights from distributed and diverse data sources in real time through a host of robust and resilient infrastructures and practices. The realisable inputs and information being drawn from water-related data heap contribute enormously in achieving more with less and to guarantee enhanced safety and security for total human society. Especially as the green movement is taking shape across the globe, there is a definite push from different quarters on water and ecology professionals to contribute their mite immensely and immediately in permanently arresting the ecological degradation. In this chapter, we have set the context by incorporating some case studies that detail how SOA has been a tangible enabler of hydroinformatics. Further down, we have proceeded by explaining how SOA-sponsored integration concepts contribute towards integrating different data for creating unified and synchronized views and to put the solid and stimulating base for quickly deriving incisive and decisive insights in the form of hidden patterns, predictions, trends, associations, tips, etc. from the integrated and composite data. This enables real-time planning of appropriate countermeasures, tactics as well as strategies to put the derived in faster activation and actuation modes. Finally the idea is to close this chapter with an overview of how SOA celebrates in establishing adaptive, on-demand and versatile SOHI platforms. SOA is insisted as the chief technique for developing and deploying agile, adaptive, and on-demand hydrology intelligence platforms as a collection of interoperable, reusable, composable, and granular hydrology and technical services. The final section illustrates the reference architecture for the proposed SOHI platform.

Business Intelligence and Service-oriented Architecture: A Delphi Study

2010 ◽  
Vol 27 (2) ◽  
pp. 168-187 ◽  
Author(s):  
Roland M. Müller ◽  
Sefan Linders ◽  
Luís Ferreira Pires
Keyword(s):  
Business Intelligence ◽  
Delphi Study ◽  
Service Oriented Architecture ◽  
Service Oriented
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