Relevant bibliographies by topics / IBM Cognos Business Intelligence

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'IBM Cognos Business Intelligence'

Author: Grafiati
Published: 4 June 2021
Last updated: 5 February 2022

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Journal articles on the topic "IBM Cognos Business Intelligence"

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Hayman, I. "Review: Business Intelligence: The IBM Solution." Computer Bulletin 42, no. 1 (January 1, 2000): 30–31. http://dx.doi.org/10.1093/combul/42.1.30-c.

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Sousa, Maria José, and Ivo Dias. "Business Intelligence for Human Capital Management." International Journal of Business Intelligence Research 11, no. 1 (January 2020): 38–49. http://dx.doi.org/10.4018/ijbir.2020010103.

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This article presents the results of an exploratory study of the use of business intelligence (BI) tools to help to make decisions about human resources management in Portuguese organizations. The purpose of this article is to analyze the effective use of BI tools in integrating reports, analytics, dashboards, and metrics, which impacts on the decision making the process of human resource managers. The methodology approach was quantitative based on the results of a survey to 43 human resource managers and technicians. The data analysis technique was correlation coefficient and regression analysis performed by IBM SPSS software. It was also applied qualitative analysis based on a focus group to identify the impacts of business intelligence on the human resources strategies of Portuguese companies. The findings of this study are that: business intelligence is positively associated with HRM decision-making, and business intelligence will significantly predict HRM decision making. The research also examines the process of the information gathered with BI tools from the human resources information system on the decisions of the human resources managers and that impacts the performance of the organizations. The study also gives indications about the practices and gaps, both in terms of human resources management and in processes related to business intelligence (BI) tools. It points out the different factors that must work together to facilitate effective decision-making. The article is structured as follows: a literature review concerning the use of the business intelligence concept and tools and the link between BI and human resources management, methodology, and the main findings and conclusions.
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Seyal, Afzaal H., Taha Afzaal, and Susan Chin T. Saun. "Assessing Emotional Intelligence and Organizational Citizenship Behavior among Executives: Examples from Bruneian SMEs." International Business Management 6, no. 4 (April 1, 2012): 476–86. http://dx.doi.org/10.3923/ibm.2012.476.486.

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Chornous, Galyna O., and Viktoriya L. Gura. "Integration of Information Systems for Predictive Workforce Analytics: Models, Synergy, Security of Entrepreneurship." European Journal of Sustainable Development 9, no. 1 (February 1, 2020): 83. http://dx.doi.org/10.14207/ejsd.2020.v9n1p83.

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The era of information economy leads to redesigning not only business models of organizations but also to rethinking the human resources paradigm to harness the power of state-of-the-art technology for Human Capital Management (HCM) optimization. Predictive analytics and computational intelligence will bring transformative change to HCM. This paper deals with issues of HCM optimization based on the models of predictive workforce analytics (WFA) and Business Intelligence (BI). The main trends in the implementation of predictive WFA in the world and in Ukraine, as well as the need to protect business data for security of entrepreneurship and the tasks of predictive analysis in the context of proactive HCM were examined. Some models of effective integration of information systems for predictive WFA were proposed, their advantages and disadvantages were analyzed. These models combine ERP, HCM, BI, Predictive Analytics, and security systems. As an example, integration of HCM system, the analytics platform (IBM SPSS Modeler), BI system (IBM Planning Analytics), and security platform (IBM QRadar Security Intelligence Platform) for predicting the employee attrition was shown. This integration provides a cycle ‘prediction – planning – performance review – causal analysis’ to support protected data-driven decision making in proactive HCM The results of the research support ensuring the effective management of all spectrum of risks associated with the collection, storage and use of data. Keywords: Workforce Analytics (WFA), Human Capital Management (HCM), Predictive Analytics, Proactive Management, BI, Information Systems (IS), Integration, Security of Entrepreneurship
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Fathi Aldiabat, Bassam. "The Impact of Emotional Intelligence in the Leadership Styles from the Employees Point View in Jordanian Banks." International Business Management 13, no. 1 (October 20, 2019): 14–20. http://dx.doi.org/10.36478/ibm.2019.14.20.

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Hart, David. "Red, White, and “Big Blue”: IBM and the Business-Government Interface in the United States, 1956–2000." Enterprise & Society 8, no. 1 (March 2007): 1–34. http://dx.doi.org/10.1017/s1467222700008764.

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This article describes the evolution of IBM's effort to manage its relationships with the U.S. government from the time that Thomas Watson, Jr. became CEO. While the Watson family controlled the firm, the family members served as the main bridges between IBM and the government. This personalized approach began to give way in the 1960s, as the intensity and scope of pressure from the firm's political environment grew beyond the capability of any individual to handle. During the 1970s and 1980s, IBM constructed a managerial hierarchy, with a newly opened Washington office at its center, which could gather more detailed intelligence and execute more sophisticated political strategies. The firm's crisis in the early 1990s provoked a second major restructuring of the interface, as IBM became more of a Washington “special interest.” Yet, some traces of the Watson imprint remained, even in the Gerstner era. Tracing IBM's evolution helps us to understand better the broader interactions between U.S. firms and their environments in this period. These interactions entailed adaptation by firms to environmental change but also efforts by firms to exert control over external forces, including public policy.
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Ramalu, Subramaniam Sri, Faridahwati Mohd Shamsudin, and Chandrakantan Subramania. "The Mediating Effect of Cultural Intelligence on the Relationship Between Openness Personality and Job Performance among Expatriates on International Assignments." International Business Management 6, no. 5 (May 1, 2012): 601–10. http://dx.doi.org/10.3923/ibm.2012.601.610.

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Graphics, Inc, Silicon. "IBM DB2 Universal Database and SGI Altix: Identity Resolution and Business Intelligence for an Uncertain World." Computational Methods in Science and Technology Special Issue, no. 1 (2006): 93–99. http://dx.doi.org/10.12921/cmst.2006.si.01.93-99.

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Singh, N. P., and Mohammad Jaffer Nayeem M. "Critical Analysis of Expansion Strategies of SAP, IBM, Oracle and Microsoft in the area of Business Intelligence." International Journal of Strategic Information Technology and Applications 2, no. 2 (April 2011): 23–43. http://dx.doi.org/10.4018/jsita.2011040103.

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Business Intelligence (BI) industry has emerged as a high growth area. Recognizing this fact, both pure play vendors as well as big application and infrastructure vendors are trying different strategies to increase their market shares. The paper starts with a discussion of BI industry since 2002 to understand the underlying dynamics of the BI industry. It is followed by analysis of BI growth strategies of big four application and infrastructure vendors—SAP, IBM, Oracle, and Microsoft—to get a bigger pie of the market. The paper also analyzes the customer reactions to the new BI paradigm, impact of the acquisition on BI market and concluding remarks on the acquisition of pure play vendors by big four.
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Gupta, Arvind, Biplav Srivastava, Daby Sow, Ching-Hua Chen, and Oshani Seneviratne. "Reflections on the Ingredients for Success in AI Research: An Interview with Arvind Gupta." AI Magazine 40, no. 4 (November 20, 2019): 24–27. http://dx.doi.org/10.1609/aimag.v40i4.5187.

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This article contains the observations of Arvind Gupta, who has over 22 years of experience in leadership, policy, and entrepreneurial roles, in both the Silicon Valley and India. Gupta was recently interviewed about the factors that could influence successful artificial intelligence research. At the time of the interview, Gupta was the chief executive officer of MyGov, India. During our interview, he shared with the editorial team his perspectives on investing in artificial intelligence innovations for business and society, in India. The interviewers included members of the special track edito­rial team from IBM (Biplav Srivastava, Daby Sow, and Ching-Hua Chen) and Rensselaer Polytechnic Institute (Oshani Seneviratne).
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Dissertations / Theses on the topic "IBM Cognos Business Intelligence"

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Lelek, Roman. "Srovnání platformy IBM Cognos BI s Pentaho." Master's thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-114266.

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There are two different types of platforms in the world of business intelligence - commercial and open source. The main objective of this thesis is to compare two representatives of both worlds - IBM Cognos BI version 10 and Pentaho BI Suite 4.1. This thesis is focused on the theoretical comparison of platforms according to defined benchmarks. Practical application of both platforms is described on example of model company MATASTAV. In the introduction the main topic, objectives and benefits are defined. Then it is necessary to describe expressions that may occur on following pages. The initial situation is defined by example of company MATASTAV. Both platforms are introduced in the next part and then are defined benchmarks with selected method of comparison. Platforms are theoretically and practically compared on following parts of this thesis. Conclusion contains results from both comparisons. Major benefit of this thesis is based on the practical comparison of both platforms on the example company MATASTAV and gathering of personal experiences and problems solved.
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Novák, Ondřej. "Srovnání BI platforem IBM Cognos a SAP BO." Master's thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-81969.

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Business Intelligence platforms contain many detailed tools with overlapping functionality. The primary aim of this thesis is to compare two BI platforms from leaders in the market - IBM Cognos BI (version 10) and SAP Business Objects (version 3.1). This comparison emphasises their practical usefulness in both ad hoc and standard reporting. In the first theoretical chapter there is a definition of basic terms and a brief description of the BI solution. In the following two chapters there are detailed descriptions of IBM Cognos BI and SAP Business Objects platforms including the most important tools. The theoretical part of this thesis is based mostly on documentation. The practical part of this thesis defines criteria for the evaluation of BI platforms. Following this chapter is the main comparison based mostly on my practical experience with each tool and experience from a migration project from IBM Cognos to SAP BO. Workarounds are described in some cases to compensate for missing functionality. The results this thesis are evaluation criteria as well as a description and comparison of both platforms. The merit of this thesis is an identification of problematic functionality present in BI solutions from the points of view of new development, implementation and migration.
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Kryszczuk, Darius. "Návrh prezentace metadat reportů z IBM Cognos BI." Master's thesis, Vysoká škola ekonomická v Praze, 2014. http://www.nusl.cz/ntk/nusl-198465.

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Dramatic increasing of amount of data in running a business has been consireded a typical phenomenon of the last decade. This fact, however, has its impact on the business planning and decision making. The area, which deals with this problematics, is called Business Intelligence (BI). The problem lies in the implementation of applications directing to the BI, because it is often oriented only on isolated projects, so they cause only partial effect. In such cases, BI cannot fulfil the expected role, but still preserves the negatives instead. By saying negatives, it is meant: complicated searching for analytical outputs, significant dete-rioration of their output data, cost increase in administation of BI systems, and others. The solution can represented by integration of partial BI systems and by transfer of their BI metadata into a single informational system, serving as an "entering gate" for all the business workers. From the whole company perspective, there exist also benefits in the metadata managament, such as: determination of quality and usage of reports, prolonging of the life cycle, cooperative forming of the knowledge basis, consolidation of the terms in the business, more efficient way of browsing in the system and comprehensibility of analytical system's outputs. The aim of this diploma thesis is formation of a metadata presentation and its realization into a preselected information system, together with meeting of the advantages resulting from applying business metadata.
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Rajnoch, Adam. "Implementace podpory studia v nástroji IBM Cognos." Master's thesis, Vysoká škola ekonomická v Praze, 2012. http://www.nusl.cz/ntk/nusl-150098.

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In recent years, Business Intelligence is one of the fastest growing software industry according to foreign analyzes. More and more companies realize the importance of tools for Business Intelligence and dashboarding. That is why I chose this topic for my thesis. The main part of this thesis focuses on study support for subject 4IT314 Enterprise Information Systems. This course teaches student how to work with the ERP system Microsoft Dynamics AX. The main shortage of this subject is the lack of feedback to students. Therefore it was decide to integrate BI tools that will be used for dashboarding over database of Microsoft Dynamics AX. In the theoretical part are explains the basic terms essential to understanding BI and dashboarding. On the basis of defined criteria was chose BI tool for integration in to the subject 4IT314. In the practical part of this thesis is described the implementation of this tool and created user documentation, which is used as study materials for students.
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Espinoza, Felix. "Podpora vizualizace v self-service Business Intelligence nástrojích - porovnání SAS Visual Analytics a IBM Cognos Analytics." Master's thesis, Vysoká škola ekonomická v Praze, 2016. http://www.nusl.cz/ntk/nusl-262209.

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The thesis deals with problematics of tools marked as Self Service Business Intelligence (SSBI) which is paid close attention by its users as well as producers due to expected progressive growth of this trend. Two products are evaluated: SAS Visual Analytics and IBM Cognos Analytics, both tools are evaluated by their extent of user´s autonomy and support of data visualization. Basic principles and concepts connected to the area of business intelligence are defined in theoretical part of the thesis. The problematics of data visualization is introduced and trend of self-service business intelligence is discussed with analyzing its benefits as well as restrictions. Technological factors which helped to fast development of SSBI are mentioned as well. A methodology has been created within practical part of the thesis. It is enforceable for any other tool from the family of SSBI and it is possible to assess the extent of support within observed categories through this methodology: Using information, Creation of information, Creation of sources and Visualization. A set of criteria on basis of which the evaluator can create evaluation form corresponding to his/her needs was defined for each of the stated categories. Usability of the methodology is illustratively demonstrated at mutual comparison of chosen modules of both tools while those parts are sufficiently described before the evaluation itself.
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Zinchenko, Yulia. "IBM Cognos Report Studio as an Effective Tool for Human Capital Reporting." Master's thesis, Vysoká škola ekonomická v Praze, 2013. http://www.nusl.cz/ntk/nusl-199724.

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Main topic discussed in this diploma thesis is corporate reporting in terms of Human Capital using Business Intelligence tools, specifically IBM Cognos Report Studio. One of the objectives is to show step-by-step methodology of creating complex dynamic report, which includes data structure modeling, layout design and quality check. Another objective is to conduct Cost-Benefit Analysis for a real-life project, which is focused on recreating of Excel-based report in Cognos-based environment in order to automate information flows. Essential part of the diploma thesis is theoretical background of Business Intelligence aspects of data quality and visualization as well as purposes of human capital reporting and description of appropriate KPIs. Objectives are addressed by conducting analysis and research of resources related to topics described above as well as using IBM Cognos Report Studio provided by one of the major companies in financial advisory field. This diploma thesis represents relevant reading for those, who are interested in real-life application of data quality improvement and information flow automation using Business Intelligence reporting tools.
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Johari, Shirazi Iman. "Combining Business Intelligence, Indicators, and the User Requirements Notation for Performance Monitoring." Thesis, Université d'Ottawa / University of Ottawa, 2012. http://hdl.handle.net/10393/23540.

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Organizations use Business Intelligence (BI) systems to monitor how well they are meeting their goals and objectives. Yet, very often BI systems do not include clear models of the organization’s goals or of how to measure whether they are satisfied or not. Several researchers now attempt to integrate goal models into BI systems, but there are still major challenges related to how to get access to the BI data to populate the part of the goal model (often indicators) used to assess goal satisfaction. This thesis explores a new approach to integrate BI systems with goal models. In particular, it explores the integration of IBM Cognos Business Intelligence, a leading BI tool, with an Eclipse-based goal modeling tool named jUCMNav. jUCMNav is an open source graphical editor for the User Requirements Notation (URN), which includes the Use Case Map notation for scenarios and processes and the Goal-oriented Requirement Language for business objectives. URN was recently extended with the concept of Key Performance Indicator (KPI) to enable performance assessment and monitoring of business processes. In jUCMNav, KPIs are currently calculated or modified manually. The new integration proposed in this thesis maps these KPIs to report elements that are generated automatically by Cognos based on the model defined in jUCMNav at runtime, with minimum effort. We are using IBM Cognos Mashup Service, which includes web services that enable the retrieval of report elements at the most granular level. This transformation provides managers and analysts with useful goal-oriented and process-oriented monitoring views fed by just-in-time BI information. This new solution also automates retrieving data from Cognos servers, which helps reducing the high costs usually caused by the amount of manual work required otherwise. The novel approach presented in this thesis avoids manual report generation and minimizes any contract with respect to the location of manually created reports, hence leading to better usability and performance. The approach and its tool support are illustrated with an ongoing example, validated with a case study, and verified through testing.
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Růžičková, Lucie. "Rozšíření projektu vývoje aplikačního SW systému v bankovní instituci o BI nadstavbu." Master's thesis, Vysoká škola ekonomická v Praze, 2017. http://www.nusl.cz/ntk/nusl-358908.

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The aim of this thesis is to implement Business Intelligence solution in the investment banking sector. The first part of this thesis is focused on general use of Business Intelligence in the banking sector and future developments in this area. Further it defines the objectives and reasons for the implementation of BI in the areas of investment banking. This part also explains basic terms used in investment banking which occur in the thesis and introduces a project in which the Business Intelligence is implemented. The second part focuses on determination of requirements and their analysis from which the data warehouse design is derived. Another part deals with the implementation of the designed data warehouse and ETL packages for loading the data. Further the tool in which the reports are created is described by exemplary implementation of the reports. In the last part of this thesis the implemented BI solution is evaluated by the users.
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Fargačová, Tamara. "Komparace funkcionality standardní BI platformy a BI modulu integrovaného v ERP systému." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2018. http://www.nusl.cz/ntk/nusl-378368.

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This master’s thesis deals with comparison of the standard Business Intelligence platform specifically IBM Cognos BI and BI module integrated in the ERP system QI. In the first part it defines basic concepts of this topic and describes the life cycle of business information systems with emphasis on Business Intelligence. In the next part current situation on the market of these platforms and BI tools which create management information systems is described. Both types of BI solutions are compared with concentration on standard functionality usage. It also describes their ability to analyze through using data warehouse technology, integration with third-party products and business and economic aspects.
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VENKATESH, UMA DEVI. "QUALTITATIVE ANALYSIS OF BUSINESS INTELLIGENCE : BUSINESS INTELLIGENCE FOR IBM WITH SMARTER SELF-SERVICE ANALYTICS." Thesis, Högskolan i Halmstad, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-33524.

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Books on the topic "IBM Cognos Business Intelligence"

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Volitich, Dan. IBM Cognos 8 Business Intelligence. New York: McGraw-Hill, 2008.

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IBM Cognos 8 Business Intelligence: The official guide. New York: McGraw-Hill, 2008.

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Garg, Ankit. IBM Cognos Business Intelligence 10. 1 Dashboarding Cookbook. Birmingham: Packt Publishing, Limited, 2012.

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Gerard, Ruppert, ed. IBM Cognos Business Intelligence 10: The official guide. New York: McGraw-Hill, 2012.

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Filip, Draskovic, ed. IBM Cognos 10 Report Studio: Practical examples. Indianapolis: IBM Press, 2012.

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International Business Machines Corporation. International Technical Support Organization, ed. Leveraging IBM Cognos 8 BI for Linux on IBM System z. [Poughkeepsie, NY]: IBM, International Technical Support Organization, 2010.

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IBM Cognos TM1 cookbook: Build real world planning, budgeting, and forecasting solutions with a collection of 60 simple but incredibly effective recipes. Birmingham, UK: Packt Publishing, 2011.

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Jochen, Gruenes, and Ilacqua Christopher, eds. IBM Cognos TM1: The official guide. New York: McGraw-Hill, 2012.

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Padilla, Juan A. Cognos 8 BI for consumers: A step-by-step introductory guide to Cognos Connection. Guaynabo, PR: Technology Partners Books, 2007.

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Inc, ebrary, ed. IBM Cognos 8 Report Studio cookbook: Over 80 great recipes for taking control of Cognos 8 Report Studio. Birmingham, U.K: Packt Enterprise, 2010.

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Book chapters on the topic "IBM Cognos Business Intelligence"

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Pirk, Kay, and Volkhard Wolf. "Business Intelligence von IBM." In Data Warehouse Managementhandbuch, 207–33. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-642-56847-3_11.

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Bernardino, Jorge, Joaquim Lapa, and Ana Almeida. "Commercial and Open Source Business Intelligence Platforms for Big Data Warehousing." In Emerging Perspectives in Big Data Warehousing, 158–81. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-5516-2.ch007.

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A big data warehouse enables the analysis of large amounts of information that typically comes from the organization's transactional systems (OLTP). However, today's data warehouse systems do not have the capacity to handle the massive amount of data that is currently produced. Business intelligence (BI) is a collection of decision support technologies that enable executives, managers, and analysts to make better and faster decisions. Organizations must make good use of business intelligence platforms to quickly acquire desirable information from the huge volume of data to reduce the time and increase the efficiency of decision-making processes. In this chapter, the authors present a comparative analysis of commercial and open source BI tools capabilities, in order to aid organizations in the selection process of the most suitable BI platform. They also evaluated and compared six major open source BI platforms: Actuate, Jaspersoft, Jedox/Palo, Pentaho, SpagoBI, and Vanilla; and six major commercial BI platforms: IBM Cognos, Microsoft BI, MicroStrategy, Oracle BI, SAP BI, and SAS BI & Analytics.
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Kamali, Amin, Gregory S. Richards, Bijan Raahemi, and Mohammad H. Danesh. "A Framework and Architecture for Performance Management in Virtual Organizations." In Advances in Business Strategy and Competitive Advantage, 1–20. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-5718-0.ch001.

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Virtual organizations are becoming common in the new world of work characterized by modern data exchange capabilities. These organizations face new challenges in information sharing that traditional approaches cannot address. This research proposes a framework and architecture for providing performance data to partners in virtual organizations. The framework aligns the activities of partners in a virtual organization at three different layers and defines common performance measurement indicators at each layer. It also proposes an implementation architecture that enables inter-organizational performance management in collaborative environments. The proposed architecture is validated through a prototype developed using IBM business process and business intelligence products.
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Xu, Lai, and Paul de Vrieze. "E-Contracting Challenges." In Electronic Services, 1620–29. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-61520-967-5.ch099.

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A decade ago, IT — through its innovations in business process reengineering — led the way in breaking down the inefficiencies within companies. Firms in the new millennium now face relentless pressure to perform better, faster, cheaper, while maintaining a high level of guaranteed results. Firms must thus focus on their core competencies and outsource all other activities. Working with a partner, however, requires breaking down the inefficiencies between organizations and coping with frequent change across the entire end-to-end value chain. In this new world of collaborative commerce and collaborative souring, a standard business process is simply inadequate. Using e-contracts to build new business relationships and to fulfill e-contracts through the Internet are important trends. E-contracting is however not a new concept. The history of e-contracting can be reviewed from legal and technology aspects. Over the last 20 years or so, a growing body of research in artificial intelligence has focused on the representation of legislation and regulations (Sergor, 1991). As specific regulations, contracts are used to regulate the actions of twoor multi-party interactions. Gardner (1987) has developed contract formation rules. Her work concerns legislation about the nature of exchanges that lead to contractual relations. The ALDUS project and Legal Expert project investigated drafting the Sale Goods contract (ALDUS, 1992) and the United Nations Convention on contracts for the international sale of goods (Yoshino 1997, 1998), respectively. Detailed information on developing logic-based tools for the analysis and representation of legal contracts can be found in Daskalopulu (1997, 1999). The law regards contracts as collections of obligations; research in this area includes automated inference methods, which are intended to facilitate application of the theory to the analysis of practical problems. The purpose of a legal e-contracting system is to clarify and expand an incomplete and imprecise statement of requirements into a precise formal specification. In the early 1990s, the development of EDI (electronic data interchange) was a significant movement for electronic commerce. EDI was considered a term that refers solely to electronic transactions and contracts (Justice Canada, 1995). EDI requires an agreement between trading partners that not only dictates a standard data format for their computerto- computer communications, but also governs all related legal issues of EDI usage. In 1987, the first set of EDI rules was named the Uniform Rules of Conduct for Interchange of Trade Data by Teletransmission (UNCID, 1987). In 1990, the American Bar Association (ABA) published a Model Trading Partner Agreement and Commentary, together with an explanatory report (Winn & Wright, 2001). In 2000 IBM submitted to OASIS (for standardization) the first example of an XML-based EDI TPA language, called Trading Partner Agreement Markup Language (tpaML). While the EDI standard introduced efficient communication channels between companies, its implementation was not widely accepted due to its high installation costs, lack of flexibility, and technological limitations (Raman, 1996). With the development of the Internet, electronic contracting began to be interpreted in broader terms. In this new view, an e-contract is not only used as a legally binding agreement between a buyer and seller, but it can also used across different workflow systems to cross different organizational business processes (Koetsier, Grefen, & Vonk, 1999; Kafeza, Chiu, & Kafeza, 2001; Cheung, Chiu & Till, 2002) to integrate different Web services (Cheung et al., 2002, 2003). E-contracting has become synonymous with business integration over electronic networks.
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Conference papers on the topic "IBM Cognos Business Intelligence"

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Khalid, Rakan, Ian Cloves, and Sydney Yip. "Introduction to IBM Cognos 8 business intelligence." In the 2010 Conference of the Center for Advanced Studies. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1923947.1923986.

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Miskuf, Martin, Iveta Zolotova, and Michael Nemcik. "Application of business intelligence solutions from microsoft and IBM on manufacturing data." In 2016 IEEE 14th International Symposium on Applied Machine Intelligence and Informatics (SAMI). IEEE, 2016. http://dx.doi.org/10.1109/sami.2016.7422979.

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Rizvi, Haider, Joyce Coleman, and Sam Lightstone. "Poster session: Simplifying business intelligence with a hybrid appliance: the IBM balanced warehouse." In 2008 IEEE 24th International Conference on Data Engineeing workshop (ICDE Workshop 2008). IEEE, 2008. http://dx.doi.org/10.1109/icdew.2008.4498287.

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Popa, Andrei, Ben Amaba, and Jeff Daniels. "A Framework of Best Practices for Delivering Successful Artificial Intelligence Projects. A Case Study Demonstration." In SPE Annual Technical Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/206014-ms.

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Abstract A practical framework that outlines the critical steps of a successful process that uses data, machine learning (Ml), and artificial intelligence (AI) is presented in this study. A practical case study is included to demonstrate the process. The use of artificial intelligent and machine learning has not only enhanced but also sped up problem-solving approaches in many domains, including the oil and gas industry. Moreover, these technologies are revolutionizing all key aspects of engineering including; framing approaches, techniques, and outcomes. The proposed framework includes key components to ensure integrity, quality, and accuracy of data and governance centered on principles such as responsibility, equitability, and reliability. As a result, the industry documentation shows that technology coupled with process advances can improve productivity by 20%. A clear work-break-down structure (WBS) to create value using an engineering framework has measurable outcomes. The AI and ML technologies enable the use of large amounts of information, combining static & dynamic data, observations, historical events, and behaviors. The Job Task Analysis (JTA) model is a proven framework to manage processes, people, and platforms. JTA is a modern data-focused approach that prioritizes in order: problem framing, analytics framing, data, methodology, model building, deployment, and lifecycle management. The case study exemplifies how the JTA model optimizes an oilfield production plant, similar to a manufacturing facility. A data-driven approach was employed to analyze and evaluate the production fluid impact during facility-planned or un-planned system disruptions. The workflows include data analytics tools such as ML&AI for pattern recognition and clustering for prompt event mitigation and optimization. The paper demonstrates how an integrated framework leads to significant business value. The study integrates surface and subsurface information to characterize and understand the production impact due to planned and unplanned plant events. The findings led to designing a relief system to divert the back pressure during plant shutdown. The study led to cost avoidance of a new plant, saving millions of dollars, environment impact, and safety considerations, in addition to unnecessary operating costs and maintenance. Moreover, tens of millions of dollars value per year by avoiding production loss of plant upsets or shutdown was created. The study cost nothing to perform, about two months of not focused time by a team of five engineers and data scientists. The work provided critical steps in "creating a trusting" model and "explainability’. The methodology was implemented using existing available data and tools; it was the process and engineering knowledge that led to the successful outcome. Having a systematic WBS has become vital in data analytics projects that use AI and ML technologies. An effective governance system creates 25% productivity improvement and 70% capital improvement. Poor requirements can consume 40%+ of development budget. The process, models, and tools should be used on engineering projects where data and physics are present. The proposed framework demonstrates the business impact and value creation generated by integrating models, data, AI, and ML technologies for modeling and optimization. It reflects the collective knowledge and perspectives of diverse professionals from IBM, Lockheed Martin, and Chevron, who joined forces to document a standard framework for achieving success in data analytics/AI projects.
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