scholarly journals DATA WAREHOUSING APPLICATIONS: AN ANALYTICAL TOOL FOR DECISION SUPPORT SYSTEM

2014 ◽  
pp. 294-299
Author(s):  
MOHAMMED SHAFEEQ AHMED
Keyword(s):  
Data Mining ◽  
Decision Support ◽  
Data Storage ◽  
Data Warehousing ◽  
Transaction Processing ◽  
Multidimensional Data ◽  
Data Warehouses ◽  
On Line ◽  
Analytical Processing ◽  
On Line Analytical Processing

Data-driven decision support systems, such as data warehouses can serve the requirement of extraction of information from more than one subject area. Data warehouses standardize the data across the organization so as to have a single view of information. Data warehouses (DW) can provide the information required by the decision makers. The data warehouse supports an on-line analytical processing (OLAP), the functional and performance requirements of which are quite different from those of the on-line transaction processing (OLTP) applications traditionally supported by the operational databases. Data warehouses provide on-line analytical processing (OLAP) tools for the interactive analysis of multidimensional data of varied granularities, which facilitates effective data mining. Data warehousing and OLAP have emerged as leading technologies that facilitate data storage, organization and then, significant retrieval. Both are essential elements of decision support, which has increasingly become a focus of the database industry. This paper provides a detailed picture of Data warehousing (DW), exploring the features of it, applications and the architecture of DW over Data Mining, Online Analytical Processing (OLAP), On-line Transaction Processing (OLTP) technologies.

On-Line Analytical Processing at Washtenaw Mortgage

2011 ◽  
pp. 196-216
Author(s):  
John H. Heinrichs ◽  
William J. Doll
Keyword(s):  
Information Systems ◽  
Market Analysis ◽  
Ease Of Use ◽  
Executive Information Systems ◽  
Analysis Application ◽  
On Line ◽  
Stage Process ◽  
Analytical Processing ◽  
On Line Analytical Processing ◽  
Strategic Market

In an ever-changing, competitive marketplace, executive information systems (EIS) promise the ability to simultaneously assess factors in both the internal and external environment, enabling a timely competitive response. EIS are enjoying a renaissance due to the recent emergence of on-line analytical processing (OLAP) capabilities. OLAPs power, flexibility and ease of use supports mental model (knowledge) creation better than traditional executive information systems. This case study allows you to examine the usefulness and ease of use of OLAP technology for strategic market analysis at Washtenaw Mortgage Company, a firm in the mortgage wholesale industry. The key to improving competitive performance is not the technology, but rather, how the technology is utilized to focus managements analysis. Gaining strategic insights requires three ingredients people, process, and technology. A three-stage process used for implementing an OLAP strategic market analysis application is presented. OLAP technology marks an evolutionary improvement in EIS software. The potential of this technology, however, is not likely to be realized without a better understanding of the process for achieving management focus.

On-Line Analytical Processing at Washtenaw Mortgage Company

2011 ◽  
pp. 196-216
Author(s):  
John H. Heinrichs ◽  
William J. Doll
Keyword(s):  
Information Systems ◽  
Market Analysis ◽  
Ease Of Use ◽  
Executive Information Systems ◽  
Analysis Application ◽  
On Line ◽  
Stage Process ◽  
Analytical Processing ◽  
On Line Analytical Processing ◽  
Strategic Market

In an ever-changing, competitive marketplace, executive information systems (EIS) promise the ability to simultaneously assess factors in both the internal and external environment, enabling a timely competitive response. EIS is enjoying a renaissance due to the recent emergence of on-line analytical processing (OLAP) capabilities. OLAP’s power, flexibility and ease of use supports mental model (knowledge) creation better than traditional executive information systems. This case study allows you to examine the usefulness and ease of use of OLAP technology for strategic market analysis at “Washtenaw Mortgage Company”, a firm in the mortgage wholesale industry. The key to improving competitive performance is not the technology, but rather, how the technology is utilized to focus management’s analysis. Gaining strategic insights requires three ingredients – people, process, and technology. A three-stage process used for implementing an OLAP strategic market analysis application is presented. OLAP technology marks an evolutionary improvement in EIS software. The potential of this technology, however, is not likely to be realized without a better understanding of the process for achieving management focus.

Closing Ontologies to Define OLAP Systems

2014 ◽  
Vol 4 (4) ◽  
pp. 1-16
Author(s):  
Manuel Torres ◽  
José Samos ◽  
Eladio Garví
Keyword(s):  
Domain Ontology ◽  
The Other ◽  
Other Hand ◽  
On Line ◽  
Analytical Processing ◽  
On Line Analytical Processing ◽  
Basic Approaches ◽  
The One

Ontologies can be used in the construction of OLAP (On-Line Analytical Processing) systems. In such a context, ontologies are mainly used either to enrich cube dimensions or to define ontology based-dimensions. On the one hand, if dimensions are enriched using large ontologies, like WordNet, details that are beyond the scope of the dimension may be added to it. Even, dimensions may be obscured because of the massive incorporation of related attributes. On the other hand, if ontologies are used to define a dimension, it is possible that a simplified version of the ontology is needed to define the dimension, especially when the used ontology is too complex for the dimension that is being defined. These problems may be solved using one of the existing mechanisms to define ontology views. Therefore, concepts that are not needed for the domain ontology are kept out of the view. However, this view must be closed so that, no ontology component has references to components that are not included in the view. In this work, two basic approaches are proposed: enlargement and reduction closure.

Basic Notions on Multidimensional Aggregate Data

2005 ◽  
pp. 211-216
Author(s):  
Maurizio Rafanelli
Keyword(s):  
Economic Analysis ◽  
Statistical Data ◽  
Aggregate Data ◽  
Data Cube ◽  
Application Field ◽  
Business Analysis ◽  
On Line ◽  
Analytical Processing ◽  
On Line Analytical Processing ◽  
New Applications

The term multidimensional aggregate data (MAD; see Rafanelli, 2003) generally refers to data in which a given fact is quantified by a set of measures obtained applying one more or less complex aggregative function (count, sum, average, percent, etc.) to row data, measures that are characterized by a set of variables, called dimensions. MAD can be modeled by different representations, depending on the application field which uses them. For example, some years ago this term referred essentially to statistical data, that is, data whose use is essentially of socio-economic analysis. Recently, the metaphor of the data cube was taken up again and used for new applications, such as On-Line Analytical Processing (OLAP), which refer to aggregate and non aggregate data for business analysis.

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