Integration of Data Warehouse into Knowledge-based System on Construction Management Decision Making

2003 ◽  
Vol 10 (1) ◽  
pp. 8-13
Author(s):  
K W Chau ◽  
M Anson ◽  
Cao Ying ◽  
Zhang Jianping
Keyword(s):  
Decision Making ◽  
Data Warehouse ◽  
Construction Management ◽  
Management Decision ◽  
Knowledge Based System ◽  
Knowledge Based ◽  
Management Decision Making

Physical Data Warehousing Design

2011 ◽  
pp. 906-911 ◽  
Author(s):  
Ladjel Bellatreche ◽  
Mukesh Mohania
Keyword(s):  
Decision Making ◽  
Data Warehouse ◽  
Historical Data ◽  
Data Warehousing ◽  
Management Decision ◽  
Materialized Views ◽  
Performance Goal ◽  
Interactive Nature ◽  
Management Decision Making ◽  
Using Data

Recently, organizations have increasingly emphasized applications in which current and historical data are analyzed and explored comprehensively, identifying useful trends and creating summaries of the data in order to support high-level decision making. Every organization keeps accumulating data from different functional units, so that they can be analyzed (after integration), and important decisions can be made from the analytical results. Conceptually, a data warehouse is extremely simple. As popularized by Inmon (1992), it is a “subject-oriented, integrated, time-invariant, non-updatable collection of data used to support management decision-making processes and business intelligence”. A data warehouse is a repository into which are placed all data relevant to the management of an organization and from which emerge the information and knowledge needed to effectively manage the organization. This management can be done using data-mining techniques, comparisons of historical data, and trend analysis. For such analysis, it is vital that (1) data should be accurate, complete, consistent, well defined, and time-stamped for informational purposes; and (2) data should follow business rules and satisfy integrity constraints. Designing a data warehouse is a lengthy, time-consuming, and iterative process. Due to the interactive nature of a data warehouse application, having fast query response time is a critical performance goal. Therefore, the physical design of a warehouse gets the lion’s part of research done in the data warehousing area. Several techniques have been developed to meet the performance requirement of such an application, including materialized views, indexing techniques, partitioning and parallel processing, and so forth. Next, we briefly outline the architecture of a data warehousing system.

Projects in the Optimal Allocation and Management of Construction Equipment

2011 ◽  
Vol 120 ◽  
pp. 603-608
Author(s):  
Tian Xiong Yang ◽  
Shun Tian Yang ◽  
Mei Wu Peng
Keyword(s):  
Decision Making ◽  
Systematic Study ◽  
Construction Management ◽  
Optimal Allocation ◽  
Optimal Configuration ◽  
Construction Equipment ◽  
Management Decision ◽  
Equipment Management ◽  
Production Factors ◽  
Management Decision Making

Projects, construction equipment management is the process of the project and construction management of production factors is an important component. Construction equipment on the project configuration, use, cost accounting and other comprehensive systematic study, given the optimal configuration and dynamic management decision-making programs, to achieve their project goals.

scholarly journals CREATIVE TRANS-BORDER COOPERATION IN THE FIELD OF OPERATIONS RESEARCH AND SUSTAINABLE DEVELOPMENT IN CIVIL ENGINEERING

2021 ◽  
Vol 27 (6) ◽  
pp. 1613-1639
Author(s):  
Oleg Kapliński ◽  
Tatjana Vilutienė
Keyword(s):  
Decision Making ◽  
Sustainable Development ◽  
Operations Research ◽  
Construction Management ◽  
Operational Research ◽  
Civil Engineering ◽  
Multiple Criteria Decision Making ◽  
Management Decision ◽  
Management Decision Making ◽  
Theory Application

The paper presents an overview of the history and achievements of trans-border cooperation in the Lithuania-Germany-Poland triangle in planning instruments in Construction Management, decision-making theory, application of Operational Research, and Multiple Criteria Decision Making (MCDM) methods in Civil Engineering and sustainable development. The cooperation and results of the Colloquiums with 35 years of tradition, their multidimensional nature is underlined. The research instruments, methods, studied phenomena are reviewed and characteristic applications in engineering and economics are presented. The knowledge and combined efforts of three academic centers have created a synergy which set in motion many original methods and spectacular implementations. The Colloquium calendar and the evolution of organizational forms are presented along with the inclusion of the informal EURO Working Group on Operations Research in Sustainable Development and Civil Engineering.

Physical Data Warehousing Design

2011 ◽  
pp. 1546-1551
Author(s):  
Ladjel Bellatreche ◽  
Mukesh Mohania
Keyword(s):  
Decision Making ◽  
Data Warehouse ◽  
Historical Data ◽  
Data Warehousing ◽  
Management Decision ◽  
Materialized Views ◽  
Performance Goal ◽  
Interactive Nature ◽  
Management Decision Making ◽  
Using Data

Recently, organizations have increasingly emphasized applications in which current and historical data are analyzed and explored comprehensively, identifying useful trends and creating summaries of the data in order to support high-level decision making. Every organization keeps accumulating data from different functional units, so that they can be analyzed (after integration), and important decisions can be made from the analytical results. Conceptually, a data warehouse is extremely simple. As popularized by Inmon (1992), it is a “subject-oriented, integrated, time-invariant, nonupdatable collection of data used to support management decision-making processes and business intelligence”. A data warehouse is a repository into which are placed all data relevant to the management of an organization and from which emerge the information and knowledge needed to effectively manage the organization. This management can be done using data-mining techniques, comparisons of historical data, and trend analysis. For such analysis, it is vital that (1) data should be accurate, complete, consistent, well defined, and time-stamped for informational purposes; and (2) data should follow business rules and satisfy integrity constraints. Designing a data warehouse is a lengthy, time-consuming, and iterative process. Due to the interactive nature of a data warehouse application, having fast query response time is a critical performance goal. Therefore, the physical design of a warehouse gets the lion’s part of research done in the data warehousing area. Several techniques have been developed to meet the performance requirement of such an application, including materialized views, indexing techniques, partitioning and parallel processing, and so forth. Next, we briefly outline the architecture of a data warehousing system.

Data Management Maturity for Knowledge-Based Decision-Making

2018 ◽  
pp. 126-144 ◽  
Author(s):  
Joanna Palonka
Keyword(s):  
Decision Making ◽  
Data Management ◽  
Third Sector ◽  
Quality Data ◽  
Management Decision ◽  
Decision Making Process ◽  
Faith Based ◽  
Knowledge Based ◽  
Management Decision Making ◽  
Decision Making Processes

Nowadays, information has been recognized as a strategic asset of an organization. There are numerous best practices for ensuring good quality data and establishing data management frameworks that are required to provide quality information for the management decision-making process. Unlike most data management studies, which focus on large enterprises and SMEs, this study deals with organizations from the third sector in Poland, comprising e.g. associations, foundations, faith-based organizations, etc. The aim of the chapter is to determine the organizations' maturity level of data management for decision-making processes in management. A survey was conducted to gather data from the organizations. The chapter utilizes samples that were collected from Slaskie Voivodship. The conclusions of the present research can help in creating and implementing a model of the data-driven decision-making process so that the operations of these organizations can be enhanced and improved.

Centralization and Effectiveness of Reward Management in Multinational Enterprises

2018 ◽  
Vol 17 (2) ◽  
pp. 55-65 ◽  
Author(s):  
Michael Tekieli ◽  
Marion Festing ◽  
Xavier Baeten
Keyword(s):  
Decision Making ◽  
Social Identity Theory ◽  
Multinational Enterprises ◽  
Role Identity ◽  
Management Decision ◽  
Role Identities ◽  
Management Decision Making ◽  
New Perspective ◽  
Subsidiary Managers ◽  
The Relationship

Abstract. Based on responses from 158 reward managers located at the headquarters or subsidiaries of multinational enterprises, the present study examines the relationship between the centralization of reward management decision making and its perceived effectiveness in multinational enterprises. Our results show that headquarters managers perceive a centralized approach as being more effective, while for subsidiary managers this relationship is moderated by the manager’s role identity. Referring to social identity theory, the present study enriches the standardization versus localization debate through a new perspective focusing on psychological processes, thereby indicating the importance of in-group favoritism in headquarters and the influence of subsidiary managers’ role identities on reward management decision making.

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