A Yii-Powered Web Application to Assist Decision-Makers in Municipal Solid Waste Management

• Autorzy: Okae P. , David A.
• Języki publikacji: EN

Abstrakty

EN

This paper adopts the concepts of observatory and competitive intelligence (CI) to model a system that will generate better insights for decision-makers in the solid waste industry. The first part of this work is to design and develop a data warehouse (DWH) of solid waste statistics using data assembled from disparate sources. Our methodology of design is the entity relationship diagram (ERD) and our implementation tool is MySQL running on phpMyAdmin. The second part of our work will be to turn our developed DWH into a Web application using the Yii PHP component framework. Our findings indicated that the application of both concepts of observatory and CI lead to better insights for decision-makers and hence better organizational performance.

Słowa kluczowe

EN

observatory; competitive intelligence; decision-maker; Yii; DWH

• Wydawca: Polskie Towarzystwo Promocji Wiedzy ; Lublin University of Technology
• Czasopismo: Applied Computer Science
• Rocznik: 2016
• Tom: Vol. 12, no 2
• Strony: 33--41
• Opis fizyczny: Bibliogr. 13 poz., fig.

Twórcy

autor

Okae P.

• African University of Science & Technology (AUST), Computer Science Department, Km 10, Airport Road, Galadimawa, Abuja, Nigeria, [phone]; University of Ghana, Computer Engineering Department, Legon, Accra, Ghana

autor

David A.

• University of Lorraine, Nancy 2, Nancy, France, [phone]

Bibliografia

• [1] Feldman C., Von Halle B.: Handbook of Relational Database Design. Addison-Wesley Longman, Reading, MA, 1989.
• [2] Inmon W. H.: Building the Data Warehouse. John Wiley & Sons, Inc, New York, USA, 1992.
• [3] Inmon W. H.: Building the Data Warehouse. Wiley Publishing Inc, New York, USA, 2001.
• [4] Codd E.F.: A relational model of data for large shared data banks. Communications of the ACM, 13(6), 1970, p. 377–387.
• [5] Chen P.P.: The Entity-Relationship Model – Toward a Unified View of Data. ACM Transactions on Database Systems, 1(1), 1976, p. 9–36.
• [6] Imhoff C., Galemmo C.N., Geiger J.G.: Mastering Data Warehouse Design – Relational and Dimensional Techniques, Wiley Publishing, Indianapolis, 2003.
• [7] Imhoff C., Galemmo M., & Geiger J.G.: Comparing two data warehouse methodologies (Database and network intelligence). Database and Network Journal, 34(3), 2004, p. 3–9.
• [8] Kimball R.: The Data Warehouse Toolkit: Practical Techniques for Building Dimensional Data Warehouses. John Wiley & Sons, Inc., 1996.
• [9] Miles M. B., Huberman A. M.: Qualitative Data Analysis: An Expanded Source-book. Sage Publications Ltd, London, 1994.
• [10] Society of Competitive Intelligence Professionals. Available at www.scip.org, SCIP 2012.
• [11] Silverman D.: Doing Qualitative Research, 3rd edn, London Sage Publications Ltd, 2010.
• [12] Van Brakel P.: Innovation and Competitiveness in South Africa: The Case for Competitive Intelligence as an Instrument to make Better Use of Information. South African Journal of Information Management, 7(1), 2005.
• [13] Wong E., Katz R. H.: Logical design and schema conversion for relational and DBTG databases. ACM Digital Library, 1986, p. 395–408.

Uwagi

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę