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1860797359043117056
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INTELEK Repository
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Online Access
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https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072
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2015-11-04 14:27:47
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Restricted Document
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12401
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UniSZA
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[1] Ibraiz Tarique and Randall S. Schuller: Global Talent Management “Literature Review, Integrative Framework, and suggestion for further Research” Elsevier Journal of world business volume 45, 2010 pp122-133. [2] Peter Cappelli, “Talent Management for The 21st Century”, Harvard Business Review 2008, www.hbr.org . [3] Economist Intelligence Unit, “The CEO's role in talent management: How top executives from ten countries are nurturing the leaders of tomorrow. London”, 2006, London, The Economist. [4] Collins D.G and Mellahi, K “Strategic Talent Management: Review and Research Agenda,” Human Resource Management Review, Volume 19:4, 2009, pp304-313. [5] A. Mate, J. Trujillo, and E. de Gregorio, “Improving Maintainability of Data Warehouse Designs: Modeling Relationships between Sources and User Concepts” Proceedings of fifteenth International Workshop on Data warehouse and OLAP, 2012, pp25-23, ISBN 978-1-4503-1721-4. [6] Margy Ross, and Ralph Kimball, “Data warehouse tool kit: The Complete Guide to Dimensional Modelling” 2nd Edition; 2002, ISBN 0-471-20024-7. [7] Churk Ballard, Dirk Herreman, Don Shaun and Rhonda Bell, “Data Modelling Techniques for data warehousing” IBM International Technical Support Organization, First Edition February 1998, pp5-58. [8] Paul Williams “A short history of Data Warehousing” Data Varsity Blog, www.dataversity.net 2012, [9] John Wiley & Sons, W.H. Inmon, R.D. Hackthorn, “Building Data warehouse” 2002 [10] James Serra “Data Warehouse Architecture “Kimball and Inmon Methodologies” James Serra’s Blog, www.jamessera.com, posted march 12, 2012. [11] B.A. Devlin, RT Murphy, “An Architecture for Business and Information System” IBM System Journal Article Volume 27, no.1, page 60, 1988 [12] Zhang Dan-Ping, “A Data Warehouse Based on Human Resource Management of Performance Evaluation”, International Forum on Information Technology and Applications, 2009, ISNB 978- 7695-3600-2, IEEE [13] Alex Berson, Stephen J. Smith “Component of Data Warehouse” the administration newsletter, www.tdan.com, 1997. [14] Alberto Abello, and Oscar Romero, “A Survey of Multidimensional Modelling, Methodologies” International Journal of Data Warehousing and Mining , Volume 5(2), pp1-23, April 2009. [15] Torben Bach Pedersen, “Multidimensional Modeling”, http://www.cs.aau.dk/tbp Aalborg University, Denmark, [16] Strauch and Winter “A method for Demand – Driven information requirement analysis in data warehousing project” proceedings of 36th Hawai International Conference on System Sciences, 2003, ISBN 0-7695-1874-5, IEEE [17] Beate List, Robert M. Bruckner, Karl Machaczek, Josef Schiefer, “A Comparison of Data Warehouse Development Methodologies Case Study of the Process Warehouse”, proceedings of 13th International conference on Database and Expert System Application 2003; Vol. 2453, ISBN 978-3-540-46146-3, Springer [18] L. Venkata Subramaniam, Mukesh K. Mohania, Shajith Ikbal, Shantanu Godbole and Tanveer A. Faruquie, “Business Intelligence from Voice of Customer”, IEEE International Conference on Data Engineering, 2009, IBM India Research Lab, India 1084-4627/09. [19] Surajit Chaudhuri, Umeshwar Dayal, And Vivek Narasayya, “An overview of Business intelligence technology” ACM Review articles, 2011, Doi:10.1145/1978542.1978562. [20] Becker, B.E. and Huselid, M.A. “Strategic Human Resource Management: Wheredo we go from here?,” Journal of Management, 2006 Volume 32, pp898-925. [21] Boston Consulting Group (2007),” The Future of HR: Key Challenges Through 2015” Dusseldorf, Boston Consulting Group. [22] Pham Van Hai, Vatcharaporn Esichaikul, “A web-based decision support system for the evaluation and strategic planning using ISO 9000 factors in higher education”. VNU Journal of Science, Mathematics-Physics, 2008, Volume 24 pp197-208 [23] Kamaluddeen Magaji Doka, Fadhilah Ahmad, Syadiah Nor Wan Shamsuddin, Norliza Ghazali, Wan Suryani Wan Awang, “Integrated Decision Support System for Human Resource Selection Using TOPSIS Based Models” proceedings of 3rd international Conference on Informatics and Applications Kuala Terengannu Malaysia, 2014.
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norman
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12401 https://intelek.unisza.edu.my/intelek/pages/view.php?ref=12401 https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072 Restricted Document Article Journal image/jpeg inches 96 96 norman 759 1416 47 47 2015-11-04 14:27:47 1416x759 6702-01-FH02-FIK-15-04053.jpg UniSZA Private Access A conceptual framework for a multidimensional model of talent management data warehouse Journal of Theoretical and Applied Information Technology The modern business environment and dynamic economic situation has made the workforce and business ethics more versatile and sophisticated. This development forges a complex business atmosphere that compels industries to compete productively for sustainable growth. Thus, it becomes imperative for organizations to manage their talents (workforce) effectively to achieve sustenance in the modern economic climate. Regrettably, it has been challenging for HR managers to identify, select and retain competent individual’s that suits their industrial needs (talent management). Therefore, this paper proposes a conceptual framework for a Multidimensional Model of a Data Warehouse (DW) for Talent Management (TM). Further, a hybrid approach of multidimensional modeling will be adopted in developing the model of the DW. In addition, student personal information and academic performances from institute of higher learning across Malaysia will be used as the data sources. Similarly, industrial needs (job vacancies) outlined by Multimedia Development Corporation (MDEC) Malaysia will be considered as user requirement. The proposed DW will provide information that will facilitate direct mapping of candidate to industrial needs among other TM practices. Also, the DW will facilitate various TM related analytics using appropriate Business Intelligence tool. 80 2 Asian Research Publishing Network Asian Research Publishing Network 334-341 [1] Ibraiz Tarique and Randall S. Schuller: Global Talent Management “Literature Review, Integrative Framework, and suggestion for further Research” Elsevier Journal of world business volume 45, 2010 pp122-133. [2] Peter Cappelli, “Talent Management for The 21st Century”, Harvard Business Review 2008, www.hbr.org . [3] Economist Intelligence Unit, “The CEO's role in talent management: How top executives from ten countries are nurturing the leaders of tomorrow. London”, 2006, London, The Economist. [4] Collins D.G and Mellahi, K “Strategic Talent Management: Review and Research Agenda,” Human Resource Management Review, Volume 19:4, 2009, pp304-313. [5] A. Mate, J. Trujillo, and E. de Gregorio, “Improving Maintainability of Data Warehouse Designs: Modeling Relationships between Sources and User Concepts” Proceedings of fifteenth International Workshop on Data warehouse and OLAP, 2012, pp25-23, ISBN 978-1-4503-1721-4. [6] Margy Ross, and Ralph Kimball, “Data warehouse tool kit: The Complete Guide to Dimensional Modelling” 2nd Edition; 2002, ISBN 0-471-20024-7. [7] Churk Ballard, Dirk Herreman, Don Shaun and Rhonda Bell, “Data Modelling Techniques for data warehousing” IBM International Technical Support Organization, First Edition February 1998, pp5-58. [8] Paul Williams “A short history of Data Warehousing” Data Varsity Blog, www.dataversity.net 2012, [9] John Wiley & Sons, W.H. Inmon, R.D. Hackthorn, “Building Data warehouse” 2002 [10] James Serra “Data Warehouse Architecture “Kimball and Inmon Methodologies” James Serra’s Blog, www.jamessera.com, posted march 12, 2012. [11] B.A. Devlin, RT Murphy, “An Architecture for Business and Information System” IBM System Journal Article Volume 27, no.1, page 60, 1988 [12] Zhang Dan-Ping, “A Data Warehouse Based on Human Resource Management of Performance Evaluation”, International Forum on Information Technology and Applications, 2009, ISNB 978- 7695-3600-2, IEEE [13] Alex Berson, Stephen J. Smith “Component of Data Warehouse” the administration newsletter, www.tdan.com, 1997. [14] Alberto Abello, and Oscar Romero, “A Survey of Multidimensional Modelling, Methodologies” International Journal of Data Warehousing and Mining , Volume 5(2), pp1-23, April 2009. [15] Torben Bach Pedersen, “Multidimensional Modeling”, http://www.cs.aau.dk/tbp Aalborg University, Denmark, [16] Strauch and Winter “A method for Demand – Driven information requirement analysis in data warehousing project” proceedings of 36th Hawai International Conference on System Sciences, 2003, ISBN 0-7695-1874-5, IEEE [17] Beate List, Robert M. Bruckner, Karl Machaczek, Josef Schiefer, “A Comparison of Data Warehouse Development Methodologies Case Study of the Process Warehouse”, proceedings of 13th International conference on Database and Expert System Application 2003; Vol. 2453, ISBN 978-3-540-46146-3, Springer [18] L. Venkata Subramaniam, Mukesh K. Mohania, Shajith Ikbal, Shantanu Godbole and Tanveer A. Faruquie, “Business Intelligence from Voice of Customer”, IEEE International Conference on Data Engineering, 2009, IBM India Research Lab, India 1084-4627/09. [19] Surajit Chaudhuri, Umeshwar Dayal, And Vivek Narasayya, “An overview of Business intelligence technology” ACM Review articles, 2011, Doi:10.1145/1978542.1978562. [20] Becker, B.E. and Huselid, M.A. “Strategic Human Resource Management: Wheredo we go from here?,” Journal of Management, 2006 Volume 32, pp898-925. [21] Boston Consulting Group (2007),” The Future of HR: Key Challenges Through 2015” Dusseldorf, Boston Consulting Group. [22] Pham Van Hai, Vatcharaporn Esichaikul, “A web-based decision support system for the evaluation and strategic planning using ISO 9000 factors in higher education”. VNU Journal of Science, Mathematics-Physics, 2008, Volume 24 pp197-208 [23] Kamaluddeen Magaji Doka, Fadhilah Ahmad, Syadiah Nor Wan Shamsuddin, Norliza Ghazali, Wan Suryani Wan Awang, “Integrated Decision Support System for Human Resource Selection Using TOPSIS Based Models” proceedings of 3rd international Conference on Informatics and Applications Kuala Terengannu Malaysia, 2014.
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| spellingShingle |
A conceptual framework for a multidimensional model of talent management data warehouse
|
| summary |
The modern business environment and dynamic economic situation has made the workforce and business ethics more versatile and sophisticated. This development forges a complex business atmosphere that compels industries to compete productively for sustainable growth. Thus, it becomes imperative for organizations to manage their talents (workforce) effectively to achieve sustenance in the modern economic climate. Regrettably, it has been challenging for HR managers to identify, select and retain competent individual’s that suits their industrial needs (talent management). Therefore, this paper proposes a conceptual framework for a Multidimensional Model of a Data Warehouse (DW) for Talent Management (TM). Further, a hybrid approach of multidimensional modeling will be adopted in developing the model of the DW. In addition, student personal information and academic performances from institute of higher learning across Malaysia will be used as the data sources. Similarly, industrial needs (job vacancies) outlined by Multimedia Development Corporation (MDEC) Malaysia will be considered as user requirement. The proposed DW will provide information that will facilitate direct mapping of candidate to industrial needs among other TM practices. Also, the DW will facilitate various TM related analytics using appropriate Business Intelligence tool.
|
| title |
A conceptual framework for a multidimensional model of talent management data warehouse
|
| title_full |
A conceptual framework for a multidimensional model of talent management data warehouse
|
| title_fullStr |
A conceptual framework for a multidimensional model of talent management data warehouse
|
| title_full_unstemmed |
A conceptual framework for a multidimensional model of talent management data warehouse
|
| title_short |
A conceptual framework for a multidimensional model of talent management data warehouse
|
| title_sort |
conceptual framework for a multidimensional model of talent management data warehouse
|