4 research outputs found
Developing A New Decision Support System for University Student Recruitment
This paper investigates the practical issues surrounding the development and implementation of Decision Support Systems (DSS). The paper describes the traditional development approaches analyzing their drawbacks and introduces a new DSS development methodology.
The proposed DSS methodology is based upon four modules; needs’ analysis, data warehouse (DW), knowledge discovery in database (KDD), and a DSS module. The proposed DSS methodology is applied to and evaluated using the admission and registration functions in Egyptian Universities. The paper investigates the organizational requirements that are required to underpin these functions in Egyptian Universities. These requirements have been identified following an in-depth survey of the recruitment process in the Egyptian Universities. This survey employed a multi-part admission and registration DSS questionnaire (ARDSSQ) to identify the required data sources together with the likely users and their information needs. The questionnaire was sent to senior managers within the Egyptian Universities (both private and government) with responsibility for student recruitment, in particular admission and registration.
Further, access to a large database has allowed the evaluation of the practical suitability of using a DW structure and knowledge management tools within the decision making framework. 2000 records have been used to build and test the data mining techniques within the KDD process. The records were drawn from the Arab Academy for Science and Technology and Maritime Transport (AASTMT) students’ database (DB).
Moreover, the paper has analyzed the key characteristics of DW and explored the advantages and disadvantages of such data structures. This evaluation has been used to build a DW for the Egyptian Universities that handle their admission and registration related archival data. The decision makers’ potential benefits of the DW within the student recruitment process will be explored.
The design of the proposed admission and registration DSS (ARDSS) will be developed and tested using Cool: Gen (5.0) CASE tools by Computer Associates (CA), connected to a MS-SQL Server (6.5), in a Windows NT (4.0) environment. Crystal Reports (4.6) by Seagate will be used as a report generation tool. CLUSTAN Graphics (5.0) by CLUSTAN software will also be used as a clustering package.
The ARDSS software could be adjusted for usage in different countries for the same purpose, it is also scalable to handle new decision situations and can be integrated with other systems
Query Optimization Techniques for OLAP Applications: An ORACLE versus MS-SQL Server Comparative Study
Query optimization in OLAP applications is a novel problem. A lot of research was introduced in the area of optimizing query performance, however great deal of research focused on OLTP applications rather than OLAP. In order to reach the output results OLAP queries extensively asks the database, inefficient processing of those queries will have its negative impact on the performance and may make the results useless. Techniques for optimizing queries include memory caching, indexing, hardware solutions, and physical database storage. Oracle and MS SQL Server both offer OLAP optimization techniques, the paper will review both packages’ approaches and then proposes a query optimization strategy for OLAP applications. The proposed strategy is based on use of the following four ingredients: 1- intermediate queries; 2- indexes both BTrees and Bitmaps; 3- memory cache (for the syntax of the query) and secondary storage cache (for the result data set); and 4- the physical database storage (i.e. binary storage model) accompanied by its hardware solution
BUILDING DSS USING KNOWLEDGE DISCOVERY IN DATABASE APPLIED TO ADMISSION & REGISTRATION FUNCTIONS
This research investigates the practical issues surrounding the development and
implementation of Decision Support Systems (DSS). The research describes the traditional
development approaches analyzing their drawbacks and introduces a new DSS development
methodology. The proposed DSS methodology is based upon four modules; needs' analysis,
data warehouse (DW), knowledge discovery in database (KDD), and a DSS module.
The proposed DSS methodology is applied to and evaluated using the admission and
registration functions in Egyptian Universities. The research investigates the organizational
requirements that are required to underpin these functions in Egyptian Universities. These
requirements have been identified following an in-depth survey of the recruitment process in
the Egyptian Universities. This survey employed a multi-part admission and registration DSS
questionnaire (ARDSSQ) to identify the required data sources together with the likely users
and their information needs. The questionnaire was sent to senior managers within the
Egyptian Universities (both private and government) with responsibility for student
recruitment, in particular admission and registration.
Further, access to a large database has allowed the evaluation of the practical suitability of
using a data warehouse structure and knowledge management tools within the decision
making framework. 1600 students' records have been analyzed to explore the KDD process,
and another 2000 records have been used to build and test the data mining techniques within
the KDD process.
Moreover, the research has analyzed the key characteristics of data warehouses and explored
the advantages and disadvantages of such data structures. This evaluation has been used to
build a data warehouse for the Egyptian Universities that handle their admission and
registration related archival data. The decision makers' potential benefits of the data
warehouse within the student recruitment process will be explored.
The design of the proposed admission and registration DSS (ARDSS) will be developed and
tested using Cool: Gen (5.0) CASE tools by Computer Associates (CA), connected to a MSSQL
Server (6.5), in a Windows NT (4.0) environment. Crystal Reports (4.6) by Seagate will
be used as a report generation tool. CLUST AN Graphics (5.0) by CLUST AN software will
also be used as a clustering package.
Finally, the contribution of this research is found in the following areas:
A new DSS development methodology;
The development and validation of a new research questionnaire (i.e. ARDSSQ);
The development of the admission and registration data warehouse;
The evaluation and use of cluster analysis proximities and techniques in the KDD process
to find knowledge in the students' records;
And the development of the ARDSS software that encompasses the advantages of the
KDD and DW and submitting these advantages to the senior admission and registration
managers in the Egyptian Universities.
The ARDSS software could be adjusted for usage in different countries for the same purpose,
it is also scalable to handle new decision situations and can be integrated with other systems
Implementing a Three-Tier Data Warehouse
This paper aims at developing a 3-tier inter-universities data warehouse prototype for the Egyptian universities. The implementation scope is restricted to the student enrollment process. The bottom-up approach and the multi-tier (3-tier) client/server architecture were used to implement the proposed prototype. The implementation required a number of steps to be undertaken. First, a star schema data warehouse was built based on an operational database of a public university. Second, another star schema data warehouse was built based on an operational database of a private university. Third, data from the two warehouses were abstracted to formulate the inter-universities data warehouse (tier 3). Hence, a data cube based on the resulting interuniversities data warehouse was developed using an OLAP server (tier 2). The data cube is then accessed by a client tool (tier 1) for the purpose of query and analysis. Although two universities were used to implement the interuniversities data warehouse, this scenario could be applied with any number of universities in a quite similar way. This inter-universities prototype is scalable and flexible to retain more than two universities regardless of the size of the operational databases. The interuniversities prototype fosters the coordination between participating universities and supports the decision making process. The proposed system could be used to generate a variety of strategic reports