Flexible Data Warehouse Parameters: Toward Building an Integrated Architecture

Clinical databases have gathered a huge amount of information about patients and their medical conditions. Relationships and patterns within this data could provide new medical knowledge. Thus it is a difficult task focusing to model a data warehouse, very often, into internal structures and implementation applications. The aim of is project is to find the parameters of medical data warehouse which will be able to construct a flexible framework by analyze the approaches of data warehouse architectures and compare them regarding the cost and integrity. The proposed parameters may assist in achieving continual access to the common data warehouse. The important consideration, however, is that the clinical data record should contain not only longitudinal health summary information but also be used for business intelligence tool such as data mining and OLA

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

Designing the venue logistics management operations for a World Exposition

World Expositions, due to their size and peculiar features, pose a number of logistics challenges. This paper aims at developing a design framework for the venue logistics management (VLM) operations to replenish food products to the event site, through a combination of qualitative and quantitative research approaches. First, an in-depth interview methodology, combined with the outcomes of a literature review, is adopted for defining the key variables for the tactical and operational set-up of the VLM system. Second, a quantitative approach is developed to define the necessary logistics resources. The framework is then applied to the case of Milan 2015 World Exposition. It is the first time that such a design framework for a World Exposition is presented: the originality of this research lies in the proposal of a systematic approach that adds to the experiential practices constituting the current body of knowledge on event logistics

Semantic integrity in data warehousing : a framework for understanding : a thesis presented in partial fulfilment of the requirements for the degree of Masters of Business Studies in Information Systems at Massey University, Palmerston North, New Zealand

Data modelling has gathered an increasing amount of attention by data warehouse developers as they come to realise that important implementation decisions such as data integrity, performance and meta data management, depend on the quality of the underlying data model. Not all organisations model their data but where they do, Entity-Relationship (E-R) modelling, or more correctly relational modelling, has been widely used. An alternative, dimensional modelling, has been gaining acceptance in recent years and adopted by many practitioners. Consequently, there is much debate over which form of modelling is the most appropriate and effective. However, the dimensional model is in fact based on the relational model and the two models are not so different that a debate is necessary. Perhaps, the real focus should be on how to abstract meaning out of the data model. This research explores the importance of semantic integrity during data warehouse design and its impact on the successful use of the implemented warehouse. This has been achieved through a detailed case study. Consequently, a conceptual framework for describing semantic integrity has been developed. The purpose of the framework is to provide a theoretical basis for explaining how a data model is interpreted through the meaning levels of understanding, connotation and generation, and also how a data model is created from an existing meaning structure by intention, generation and action. The result of this exploration is the recognition that the implementation of a data warehouse may not assist with providing a detailed understanding of the semantic content of a data warehouse

Knowledge and Metadata Integration for Warehousing Complex Data

With the ever-growing availability of so-called complex data, especially on the Web, decision-support systems such as data warehouses must store and process data that are not only numerical or symbolic. Warehousing and analyzing such data requires the joint exploitation of metadata and domain-related knowledge, which must thereby be integrated. In this paper, we survey the types of knowledge and metadata that are needed for managing complex data, discuss the issue of knowledge and metadata integration, and propose a CWM-compliant integration solution that we incorporate into an XML complex data warehousing framework we previously designed.Comment: 6th International Conference on Information Systems Technology and its Applications (ISTA 07), Kharkiv : Ukraine (2007

Data warehouse - opportunity for local authorities

Local government exists in a very complex organizational environment, which has been subjected to an ever increasing pace of changes. This situation has generated a huge impact on the local government's reaction towards two major elements in is administration - decision making and technology approaching. The data warehouse technology offers a solution to this problem. But there are various obstacles that inhibit the government from adopting this technology

Integration of decision support systems to improve decision support performance

Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes