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.

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.

scholarly journals Using the movement patterns of reintroduced animals to improve reintroduction success

2014 ◽  
Vol 60 (4) ◽  
pp. 515-526 ◽  
Author(s):  
Oded Berger-TAL ◽  
David Saltz
Keyword(s):  
Decision Making ◽  
Release Site ◽  
Fallow Deer ◽  
Movement Behavior ◽  
Management Decision ◽  
Knowledge Gain ◽  
Conceptual Approach ◽  
Management Decision Making ◽  
Using Data ◽  
Reintroduction Success

Abstract Despite their importance to conservation, reintroductions are still a risky endeavor and tend to fail, highlighting the need for more efficient post-release monitoring techniques. Reintroduced animals are released into unfamiliar novel environments and must explore their surroundings to gain knowledge in order to survive. According to theory, knowledge gain should be followed by subsequent changes to the animal’s movement behavior, making movement behavior an excellent indicator of reintroduction progress. We aim to conceptually describe a logical process that will enable the inclusion of behavior (in particular, movement behavior) in management decision-making post-reintroductions, and to do so, we provide four basic components that a manager should look for in the behaviors of released animals. The suggested components are release-site fidelity, recurring locations, proximity to other individuals, and individual variation in movement behavior. These components are by no means the only possible ones available to a manager, but they provide an efficient tool to understanding animals’ decision-making based on ecological theory; namely, the exploration-exploitation trade-off that released animals go through, and which underlies their behavior. We demonstrate our conceptual approach using data from two ungulate species reintroduced in Israel: the Persian fallow deer Dama mesopotamica and the Arabian oryx Oryx leucoryx [Current Zoology 60 (4): 515–526, 2014].

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.

Emergency management decision-making during severe weather

2006 ◽  
Author(s):  
Leigh A. Baumgart ◽  
Ellen J. Bass ◽  
Brenda Philips ◽  
Kevin Kloesel
Keyword(s):  
Decision Making ◽  
Emergency Management ◽  
Severe Weather ◽  
Management Decision ◽  
Management Decision Making
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