Real-time business intelligence system architecture with stream mining

Yang, Hang; Fong, Simon

doi:10.1109/icdim.2010.5664637

Cited by 11 publications

(8 citation statements)

References 26 publications

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“…Business intelligence demands decision making as a realtime [1] process to add business agility. A new framework is proposed in [1] to make quick decisions where continuous data…”

Section: Related Workmentioning

confidence: 99%

An integrated approach to deploy data warehouse in business intelligence environment

Ghosh

Haider

Sen

2015

Proceedings of the 2015 Third International Conference on Computer, Communication, Control and Information Technology (C3IT)

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Business Intelligence (BI) provides historical, current and predictive views of business operations with the help of some technologies, that include reporting, online analytical processing, analytics, data mining, process mining, complex event processing, business performance management, benchmarking, text mining, predictive analytics and prescriptive analytics. As analytics plays a major role in BI, OLAP is an integrated part of BI in modern day business application. Data warehouse is the most popular way to design and build OLAP. Data warehouse along with ETL and reporting tools provides an integrated environment for business processing. Business processing also demands decision making system and knowledge representation. Moreover the data sources are physically distributed in different locations. Hence modern day business environment is a complex architecture with a numbers of entities. In this paper authors present an integrated architecture to manage and design business intelligence environment by co-ordinating several associated entities to achieve business agility.

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“…Business intelligence demands decision making as a realtime [1] process to add business agility. A new framework is proposed in [1] to make quick decisions where continuous data…”

Section: Related Workmentioning

confidence: 99%

An integrated approach to deploy data warehouse in business intelligence environment

Ghosh

Haider

Sen

2015

Proceedings of the 2015 Third International Conference on Computer, Communication, Control and Information Technology (C3IT)

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“…The application of BI in real-time environment has improved the business process ( Jalileh et al, 2011;Yang and Simon, 2010;Jun-Jang et al, 2003;Aciar et al, 2009;Vlad et al, 2010). The SOA with BI gives the best performance in the real-time environment ( Jalileh et al, 2011).…”

Section: Survey On Recent Research In Business Intelligencementioning

confidence: 99%

“…The SOA with BI gives the best performance in the real-time environment ( Jalileh et al, 2011). The real-time-BI systems control material and information flow between the suppliers and the end customers by providing pattern discovery, trend detection and visualization (Yang and Simon, 2010). The outcome of BI from the domains is described in Table II. Outcome:…”

Section: Survey On Recent Research In Business Intelligencementioning

confidence: 99%

A survey on recent research in business intelligence

Aruldoss

Travis

Venkatesan

2014

Journal of Enterprise Information Management

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Purpose-Business intelligence (BI) has been applied in various domains to take better decisions and it provides different level of information to its stakeholders according to the information needs. The purpose of this paper is to present a literature review on recent works in BI. The two principal aims in this survey are to identify areas lacking in recent research, thereby offering potential opportunities for investigation. Design/methodology/approach-To simplify the study on BI literature, it is segregated into seven categories according to the usage. Each category of work is analyzed using parameters such as purpose, domain, problem identified, solution applied, benefit and outcome. Findings-The BI contribution in various domains, ongoing research in BI, the convergence of BI domains, problems and solutions, results of congregated domains, core problems and key solutions. It also outlines BI and its components composition, widely applied BI solutions such as algorithm-based, architecture-based and model-based solutions. Finally, it discusses BI implementation issues and outlines the security and privacy policies adopted in BI environment. Research limitations/implications-In this survey BI has been discussed in theoretical perspective whereas practical contribution has been given less attention. Originality/value-A comprehensive survey on BI which identifies areas lacking in recent research and providing potential opportunities for investigation.

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“…The corresponding IA of realtime BI therefore must have the capabilities of integrating seamlessly the operational business processes and decision making systems whose information may be disparate and distributed. In order to support real-time data mining and generate actionable intelligence, the batch approach of traditional data mining is replaced with data stream mining that can better react in continuous flow of latest data streams [43]. To achieve this, a unified view of data across the enterprise is needed, and Enterprise Application Integration (EAI) has been used as an enabling technology for this.…”

Section: A Businessmentioning

confidence: 99%

The Six Technical Gaps between Intelligent Applications and Real-Time Data Mining: A Critical Review

Fong

Yang²

2011

JETWI

Self Cite

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Intelligent application is characterized by its ability to make decision autonomously. Some examples are distributed agents that collaboratively complete a complex task, yet each one of them is able to work and reason independently given the dynamic situation where they are in. The underlying think tank is often a collection of core mechanisms that include environment sensing, data capturing, data mining, ETL, knowledge processing, and decision making etc. All these techniques when placed and function together as a whole intelligent system, they will have to fulfill stringent deadlines imposed by the requirements of a real-time system. In the literature many research papers can be found on a wide variety of data mining techniques that enable intelligent applications operating in real-time. This report offers a critical review of the relevant literature, and contributes to the knowledge of identifying their shortcomings, so-called the technical gaps between the real-time requirements of a general intelligent system and the supporting components. A discussion follows on the possibilities of future intelligent applications that are empowered by data stream mining

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Real-time business intelligence system architecture with stream mining

Abstract: Business Intelligence (BI)

Cited by 11 publications

References 26 publications

An integrated approach to deploy data warehouse in business intelligence environment

An integrated approach to deploy data warehouse in business intelligence environment

A survey on recent research in business intelligence

The Six Technical Gaps between Intelligent Applications and Real-Time Data Mining: A Critical Review

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