Business Plus Intelligence Plus Technology Equals Business Intelligence

Yermish, Ira; Miori, Virginia M.; Yi, John C.; Malhotra, Rashmi; Klimberg, Ronald K.

doi:10.4018/jbir.2010071704

Cited by 17 publications

(5 citation statements)

References 44 publications

(31 reference statements)

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“…Moreover, the relevant human resource skillset will indicate the information, expertise, and ability for the current technology trend that focuses on the high demand for technical knowledge and communication skills. The relevant human resource skillset with information review will create actionable insights for practical, and community for continuous digital transforming and future technology transformation [33].…”

Section: B) Relevant Human Resource Skill Setmentioning

confidence: 99%

Journey of an Information System in Railway Industry development approach through an enterprise framework

Jayakrishnan

Mohamad

Yusof

2023

IRASE

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An enterprise framework based on the philosophy research approach to Information System (IS) features a holistic view in an industry that allows room for technological advancement, an industry with increasing expectations and demands for IS drives towards a more integrated framework and rethinking of the concept of delivering insightful outcomes. The specific features of IS in this study focus on the information criteria for the daily assignment of the railway industry operations through an industry enterprise framework. The study objective is to provide a comprehensive understanding of emerging knowledge from structuring IS and enterprise framework stages and their mashup characteristics in designing a model-driven development framework. The outcome will be a design of a strategic performance framework for a typical strategic performance application as the most vital outcome indicators, to focus on understanding the baseline of technology revolution (Industry Revolution 5.0) achievement to measure the transformation expected and the railway industry evaluation, based on the year-on-year target will be established. The usage of decision-making systems and strategic applications has increased massively to fulfill various kinds of purposes for organizations, businesses, and individuals. In this case, a high-quality decision-making system and strategic application are required to ensure it provides the intended functionalities.

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Section: B) Relevant Human Resource Skill Setmentioning

confidence: 99%

Journey of an Information System in Railway Industry development approach through an enterprise framework

Jayakrishnan

Mohamad

Yusof

2023

IRASE

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“…DM tools still demand heavy work in order to obtain the intended results, hence needing the knowledge of DM specialists to explore its full potential value. On the contrary, BI is rooted in industry and business (Yermish, Miori, Yi, Malhotra, & Klimberg, 2010), thus it is business oriented. As a result, BI tools are user-friendly and can easily be accessed and manipulated by business users.…”

Section: Research Problemmentioning

confidence: 99%

Closing the Gap between Data Mining and Business Users of Business Intelligence Systems

Azevedo

Santos

2012

International Journal of Business Intelligence Research

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Since Lunh first used the term Business Intelligence (BI) in 1958, major transformations happened in the field of information systems and technologies, especially in the area of decision support systems. BI systems are widely used in organizations and their importance is recognized. These systems present themselves as essential parts of a complete knowledge of business and an irreplaceable tool in the support to decision making. The dissemination of data mining (DM) tools is increasing in the BI field, as well as the acknowledgment of the relevance of its usage in enterprise BI systems. BI tools are friendly, iterative, and interactive, allowing business users an easy access. The user can manipulate directly data, having the ability to extract all the value contained into that business data. Problems noted in the use of DM in the field of BI is related to the fact that DM models are complex in order to be directly manipulated by business users, not including BI tools. The nonexistence of BI tools allowing business users the direct manipulation of DM models was identified as the problem. More of these issues, possible solutions and conclusions are presented in this article.

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“…Significant research work has been done on different aspects of data warehousing over the last one decade. Most previous work on data warehousing focused on design issues (Dey et al, 2006;Evermann, 2008;García-García & Ordonez, 2010;Storey & Goldstein, 1993), extract-transform-load (ETL) tools (Karakasidis et al, 2005;Simitsis, 2005;Rahman, 2010), data maintenance (Labio et al, 2000) strategies relating to view materialization (Agrawal et al, 1997;Lee et al, 2001;Mohania & Kambayashi, 2000), implementation issues (Widom, 1995;Schiesser, 2010;Rahman, 2007), and business intelligence (Davenport, 2010;Yermish et al, 2010;Wixom & Watson, 2010).…”

Section: Literature Researchmentioning

confidence: 99%

Agile Development in Data Warehousing

Rahman

Rutz

Akhter

2011

International Journal of Business Intelligence Research

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Traditional data warehouse projects follow a waterfall development model in which the project goes through distinct phases such as requirements gathering, design, development, testing, deployment, and stabilization. However, both business requirements and technology are complex in nature and the waterfall model can take six to nine months to fully implement a solution; by then business as well as technology has often changed considerably. The result is disappointed stakeholders and frustrated development teams. Agile development implements projects in an iterative fashion. Also known as the sixty percent solution, the agile approach seeks to deliver more than half of the user requirements in the initial release, with refinements coming in a series of subsequent releases which are scheduled at regular intervals. An agile data warehousing approach greatly increases the likelihood of successful implementation on time and within budget. This article discusses agile development methodologies in data warehousing and business intelligence, implications of the agile methodology, managing changes in data warehouses given frequent change in business intelligence (BI) requirements, and demonstrates the impact of agility on the business.

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Business Plus Intelligence Plus Technology Equals Business Intelligence

Cited by 17 publications

References 44 publications

Journey of an Information System in Railway Industry development approach through an enterprise framework

Journey of an Information System in Railway Industry development approach through an enterprise framework

Closing the Gap between Data Mining and Business Users of Business Intelligence Systems

Agile Development in Data Warehousing

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