Int. J. Bus. Intell. Res.最新文献_第10页

Agile Development in Data Warehousing 数据仓库中的敏捷开发

Int. J. Bus. Intell. Res. Pub Date : 2011-07-01 DOI: 10.4018/jbir.2011070105

Nayem Rahman, Dale Rutz, Shameem Akhter

{"title":"Agile Development in Data Warehousing","authors":"Nayem Rahman, Dale Rutz, Shameem Akhter","doi":"10.4018/jbir.2011070105","DOIUrl":"https://doi.org/10.4018/jbir.2011070105","url":null,"abstract":"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.","PeriodicalId":404696,"journal":{"name":"Int. J. Bus. Intell. Res.","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125284280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 25

Enterprise Intelligence: A Case Study and the Future of Business Intelligence 企业智能:商业智能的案例研究和未来

Int. J. Bus. Intell. Res. Pub Date : 2011-07-01 DOI: 10.4018/jbir.2011070101

J. Morabito, E. Stohr, Y. Genc

引用次数: 15

BI's Impact on Analyses and Decision Making Depends on the Development of Less Complex Applications 商业智能对分析和决策的影响取决于不太复杂的应用程序的开发

Int. J. Bus. Intell. Res. Pub Date : 2011-07-01 DOI: 10.4018/jbir.2011070104

R.c. Sawyer

引用次数: 29

IT and Business Can Succeed in BI by Embracing Agile Methodologies 通过采用敏捷方法，IT和业务可以在BI中取得成功

Int. J. Bus. Intell. Res. Pub Date : 2011-07-01 DOI: 10.4018/jbir.2011070103

Alex Gann

引用次数: 4

Business Intelligence Competency Centers: Centralizing an Enterprise Business Intelligence Strategy 商业智能能力中心:集中企业商业智能战略

Int. J. Bus. Intell. Res. Pub Date : 2011-07-01 DOI: 10.4018/jbir.2011070102

D. O'Neill

{"title":"Business Intelligence Competency Centers: Centralizing an Enterprise Business Intelligence Strategy","authors":"D. O'Neill","doi":"10.4018/jbir.2011070102","DOIUrl":"https://doi.org/10.4018/jbir.2011070102","url":null,"abstract":"Enterprises today continue to invest in business intelligence (BI) initiatives with the hope of providing a strategic advantage to their organizations. Many of these initiatives are supporting the tactical goals of individual business units and not the strategic goals of the enterprise. Although this decentralized approach provides short term gains, it creates an environment where information silos develop and the enterprise as a whole struggles to develop a single version of the truth when it comes to providing strategic information. Enterprises are turning toward a centralized approach to BI which aligns with their overall strategic goals. At the core of the centralized approach is the business intelligence competency center (BICC). This paper details why the centralized BICC approach should be considered an essential component of all enterprise BI initiatives. Examining case studies of BICC implementations details the benefits realized by real world companies who have taken this approach. It is also important to provide analysis of the two BI approaches in the areas of BI process and BI technology/data and people relations. The findings indicate the benefits of the centralized BICC outweigh the deficiencies of the decentralized approach.","PeriodicalId":404696,"journal":{"name":"Int. J. Bus. Intell. Res.","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126518799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 13

10 Principles to Ensure Your Data Warehouse Implementation is a Failure 确保数据仓库实现失败的10个原则

Int. J. Bus. Intell. Res. Pub Date : 2011-04-01 DOI: 10.4018/jbir.2011040103

Adam Hill, Thilini R. Ariyachandra, M. Frolick

引用次数: 8

Champion for Business Intelligence: SMART Goals for Business Focused and Financially Backed Results 商业智能冠军:以业务为中心的智能目标和财务支持的结果

Int. J. Bus. Intell. Res. Pub Date : 2011-04-01 DOI: 10.4018/jbir.2011040102

Irina Dymarsky

{"title":"Champion for Business Intelligence: SMART Goals for Business Focused and Financially Backed Results","authors":"Irina Dymarsky","doi":"10.4018/jbir.2011040102","DOIUrl":"https://doi.org/10.4018/jbir.2011040102","url":null,"abstract":"Although Gartnerâ€™s EXP 2006 CIO Survey ranked Business Intelligence (BI) as the top technology priority, BI projects face tough competition from other projects in IT portfolios promising more tangible financial returns (Wu & Weitzman, 2006) Two major hurdles that prevent BI projects from shining in portfolios are vague requirements and weak benefits calculations. Both can be addressed by examining and learning from a number of case studies that prove tangible ROI on BI solutions when scoped and designed with a focus on specific, measurable, achievable, results-oriented, and time bound SMART business goals. In order for BI projects to compete in IT portfolios based on financial measures, like ROI, BI champions need to approach BI requirements gathering with the goal of addressing a specific business problem as well as employ standard ways of calculating BI benefits post project go live. By examining common failures with BI requirements and case studies which demonstrate how successful BI implementations translate into tangible benefits for the organization, BI champions develop a toolkit of tips, tricks, and lessons learned for successful requirements gathering, design, implementation, and measure of business results on BI initiatives.","PeriodicalId":404696,"journal":{"name":"Int. J. Bus. Intell. Res.","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129996431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Mitigating Risk: Analysis of Security Information and Event Management 降低风险:安全信息分析和事件管理

Int. J. Bus. Intell. Res. Pub Date : 2011-04-01 DOI: 10.4018/jbir.2011040105

Ken Lozito

引用次数: 12

Uncovering Actionable Knowledge in Corporate Data with Qualified Association Rules 利用合格的关联规则发现企业数据中的可操作知识

Int. J. Bus. Intell. Res. Pub Date : 2011-04-01 DOI: 10.4018/jbir.2011040101

N. Jukic, Svetlozar Nestorov, Miguel Velasco, J. Eddington

{"title":"Uncovering Actionable Knowledge in Corporate Data with Qualified Association Rules","authors":"N. Jukic, Svetlozar Nestorov, Miguel Velasco, J. Eddington","doi":"10.4018/jbir.2011040101","DOIUrl":"https://doi.org/10.4018/jbir.2011040101","url":null,"abstract":"Association rules mining is one of the most successfully applied data mining methods in todayâ€™s business settings (e.g. Amazon or Netflix recommendations to customers). Qualified association rules mining is an extension of the association rules data mining method, that uncovers previously unknown correlations that only manifest themselves under certain circumstances (e.g. on a particular day of the week), with the goal of improving action results, e.g. turning an underperforming campaign (spread too thin over the entire audience) into a highly targeted campaign that delivers results. Such correlations have not been easily reachable using standard data mining tools so far. This paper describes the method for straightforward discovery of qualified association rules and demonstrates the use of qualified association rules mining on an actual corporate data set. The data set is a subset of a corporate data warehouse for Samâ€™s Club, a division of Wal-Mart Stores, INC. The experiments described in this paper illustrate how qualified association rules supplement standard association rules data mining methods and provide additional information which can be used to better target corporate actions.","PeriodicalId":404696,"journal":{"name":"Int. J. Bus. Intell. Res.","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133612406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 17

Business Intelligence Conceptual Model 商业智能概念模型

Int. J. Bus. Intell. Res. Pub Date : 2011-04-01 DOI: 10.4018/jbir.2011040104

Fletcher H. Glancy, S. Yadav

引用次数: 24