The Impact of Using Data Warehouse on Manpower Employment Decision Support System

2011 ◽  
Vol 383-390 ◽  
pp. 4653-4659
Author(s):  
Amro F. Alasta ◽  
Muftah A. Enaba

Since the use of computers in business world, data collection has become one of the most important issues due to the available knowledge in the data; such data has been stored in database. Database system was developed which led to the evolvement of hierarchical and relational database followed by Standard Query Language (SQL). As data size increases, the need for more control and information retrieval increase. These increases lead to the development of data mining systems and data warehouses. This paper focuses on the use of data warehouse as a supporting tool in decision making. We to study the effectiveness of data warehouse techniques in the sense of time and flexibility in our case study (Manpower Employment). The study will conclude with a comparison of traditional relational database and the use of data warehouse. The fundamental role of data warehouse is to provide data for supporting decision-making process. Data in data warehouse environment is multidimensional data store. We can simply say that data warehouse is a process not a product, for assembling and managing data from various sources for the purpose of gaining a single detailed view of part or all an establishment. The data warehouse concept has changed the nature of decision support system, by adding new benefits for improving and expanding the scope, accuracy, and accessibility of data. The warehouse is the link between the application and raw data, which is scattered in separate database but now is unified. The objectives of this work are to study the impact of using data warehouse on Manpower Employment Decision Support System, in the sense as far as the data quality concern. We will focus on the benefits gained from using data warehouse, and why it is more powerful than the use of traditional databases in decision making. The case study will be the Libyan national manpower employment agency. The data warehouse will collect database scattered from different sources in Libya in order to compare the performance and time.

Author(s):  
Jean-Fabrice Lebraty ◽  
Cécile Godé

This article explores the ability of a decision support system (DSS) to improve the quality of decision making in extreme environment. This DSS is actually based on a networked information system. Academic literature commonly mentions models of fit to explore the relationship between technology and performance, reckoning users' evaluations as a relevant measurement technique for Information System (IS) success. Although effective contributions have been achieved in measurement and exploration of fit, there have been few attempts to investigate the triangulation of fit between “Task-DSS-Decision Maker” under stressful and uncertain circumstances. This article provides new insights regarding the advantages provided by networked IS for making relevant decisions. An original case study has been conducted. It is focused on a networked decision support system called Link 16 that is used during aerial missions. This case study shows that the system improves decision making on an individual basis. Our result suggest the importance of three main fit criteria – Compliance, Complementarity and Conformity – to measure DSS performance under extreme environment and display a preliminary decisional fit model.


Author(s):  
Alberto Turón ◽  
Juan Aguarón ◽  
María Teresa Escobar ◽  
José María Moreno-Jiménez

The Precise Consistency Consensus Matrix (PCCM) is a decisional tool for AHP-Group Decision Making (AHP-GDM). Based on the initial pairwise comparison matrices of the individuals, the PCCM constructs a consensus matrix for the group using the concept of consistency. This paper presents a decision support system (PRIOR-PCCM) that facilitates the construction of the PCCM in the context of AHP-GDM, and the calculus of four indicators that allows comparison of the behaviour of group consensus matrices. PRIOR-PCCM incorporates the possibility of considering different weights for the decision makers and includes a module that permits the extension of the initial PCCM which can achieve the minimum number of non-null entries required for deriving priorities or establishing a complete PCCM matrix. It also includes two cardinal indicators for measuring consistency and compatibility and two ordinal indicators for evaluating the number of violations of consistency and priority. The paper introduces some new visualisation tools that improve comprehension of the process followed for obtaining the PCCM matrix and allow the cognitive exploitation of the results. These original contributions are illustrated with a case study.


2013 ◽  
Vol 850-851 ◽  
pp. 1048-1051
Author(s):  
Guang Yu Peng

This paper analyzes the DSS characteristics about the marketing under the internet as well as the influencing factors of the market decisions, Studying the decision-making functions of marketing decision support system DSS. It proposed the marketing DSS design, logical structure and its implementation based on a data warehouse as the center, online analysis processing and data mining as a means.


Author(s):  
Hadrian Peter ◽  
Charles Greenidge

Good database design generates effective operational databases through which we can track customers, sales, inventories, and other variables of interest. The main reason for generating, storing, and managing good data is to enhance the decision-making process. The tool used during this process is the decision support system (DSS). The information requirements of the DSS have become so complex, that it is difficult for it to extract all the necessary information from the data structures typically found in operational databases. For this reason, a new storage facility called a data warehouse has been developed. Data in the data warehouse have characteristics that are quite distinct from those in the operational database (Rob & Coronel, 2002).


2012 ◽  
Vol 2012 ◽  
pp. 1-7 ◽  
Author(s):  
Mary Fendley ◽  
S. Narayanan

Human decision makers typically use heuristics under time-pressured situations. These heuristics can potentially degrade task performance through the impact of their associated biases. Using object identification in image analysis as the context, this paper identifies cognitive biases that play a role in decision making. We propose a decision support system to help overcome these biases in this context. Results show that the decision support system improved human decision making in object identification, including metrics such as time taken to identify targets in an image set, accuracy of target identification, accuracy of target classification, and quantity of false positive identification.


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