Thesis (MTech (Business Information Systems))--Cape Peninsula University of Technology, 2016. / The emergence of big data (BD) has rendered existing conventional business intelligence (BI) tools inefficient and ineffective for real-time decision support systems (DSS). The inefficiency and ineffectiveness is perceived when business users need to make decisions based on stale and sometimes, incomplete data sets, which potentially leads to slow and poor decision making. In recent years, industry and academia have invented new technologies to process BD such as Hadoop, Spark, in-memory databases and NOSQL databases. The appearance of these new technologies have escalated to an extent, that organisations are faced with the challenge of determining most suitable technologies that are appropriate for real-time DSS requirements. Due to BD still being a new concept, there are no standard guidelines or frameworks available to assist in the evaluation and comparing of BD technologies. This research aims to explore factors that influence the selection of technologies appropriate for real-time DSSs in a BD environment. In addition, it further proposes evaluation criteria that can be used to compare and select these technologies. To achieve this aim, a literature analysis to understand the concept of BD, real-time DSSs and related technologies is conducted. Qualitative as well as quantitative research techniques are used after interviews are conducted with BI experts who have BD knowledge and experience. Experimental research in a computer laboratory is also conducted. The purpose of the interviews is to ascertain which technologies are being used for BD analytics and in addition, which evaluation criteria organisations use when choosing such a technology. Furthermore, a comparative computer laboratory experiment is conducted to compare three tools which run on Hadoop namely; Hive, Impala and Spark. The purpose of the experiment is to test if system performance is different for the three tools when analysing the same data set and the same computer resources. The impirical results reveals nine main factors which impact the selection of technologies appropriate for real-time DSS in a BD environment, and ten application independent evaluation criteria. Furthermore, the experiment results indicate that system performance in terms of latency, is significantly different among the three tools compared.

Made available in DSpace on 2014-06-11T19:30:09Z (GMT). No. of bitstreams: 0 Previous issue date: 2007-08Bitstream added on 2014-06-13T21:00:25Z : No. of bitstreams: 1 almeida_r_me_guara.pdf: 1434970 bytes, checksum: a45e1def677af7ba7d2da134164d54f6 (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Este trabalho aborda o problema de identificação dos efeitos causados por eventuais falhas no abastecimento de certos materiais ou equipamentos na linha de montagem de aeronaves. Tal problema consiste em avaliar se o atraso na disponibilidade de um determinado material pode ser absorvido pela flexibilidade existente na rede de atividades da produção. Dessa forma, foi desenvolvido um sistema de apoio à decisão para o planejamento e controle da produção, utilizando simulação de eventos discretos para avaliar se o sincronismo entre os elos da cadeia produtiva está se comportando a contento e, em caso negativo, disponibilizar informações para as correções necessárias. A grande dificuldade na modelagem do sistema está na necessidade de integração de uma complexa cadeia de suprimentos a uma grande rede de atividades necessárias à manufatura das aeronaves. Apesar da complexidade, o sistema criado é capaz de identificar antecipadamente o impacto causado na montagem pelos insumos atrasados, além de prover uma visão de quais materiais, e respectivos fornecedores, apresentam um atraso que não pode ser absorvido pelo sistema, o que facilitaria o trabalho dos gestores da cadeia de suprimentos para aumentar a robustez do sistema. / This work approaches the effects identification of problems caused by eventual fails in the provisioning of material or equipments in one assembly line of aircrafts. Such problem consists in evaluating if a delay in the availability of a material can be absorbed by the flexibility in the activities network of the production. This way, a decision support system was developed to support the planning and control of the production, using systems simulation, to evaluate if the synchronism among the links of the productive chain is behaving as necessary; in negative case, the system must to provide information for manager’s action. The great difficulty to produce a model of this system is about the necessary integration of a complex supply chain to a big activities network associate to aircrafts manufacture. In spite of that complexity, the system developed is able to identify the impact caused in the assembly line by each late input, providing a vision of which materials, and respective suppliers, have a delay that cannot be absorbed by the production line. So, this research looks for facilitate the manager works in to increase the system robustness.

M.Sc. (Computer Science) / The attitude of critics towards decision support systems vary from a major breakthrough to just another bussword. The objective of this study is to design an expert system that can advise the ignorant to design, implement and evaluate a decision support system. In chapter one criteria that will influence the design of a decision support system were identified. The four areas the were looked into: Organisational long term goals and -strategy Attitude of the people in the organization The tasks of management The problem a decision support system will be designed for. A list of 'criteria were compiled and carried forward to chapter two. In chapter two a decision support system was defined and the components of the system discussed. The influence that the criteria (of chapter one) had on the components of the decision support system were decided. Chapter three discussed a subset of a decision support system namely expert systems. This chapter were motivated by two things: The objective of this study was to design an expert system According to the definition of a decision support system (chapter two) an expert system is a subset of a decision support system. A brief description of the components of an expert system and a layout of the different rule bases were given. An implementation methodology will be discussed. In chapter four a methodology were described to measure user satisfaction after a decision support system were implemented. A summary of this chapter were accepted for publication as an article in 'Information and Systems Management'. Chapter five discussed a look into the future of decision support systems. A complete Super Intelligent System was described. Although this is fictitious it could trigger ideas for other studies.

Abstract For the past few years, electronics manufacturing may have been the victim of its own success. Unlike in heavier industries, rationalization is a concept that was unknown in the sector until only a few years ago and even now, many companies are struggling with cost-cutting measures. Production systems in electronics manufacturing need to be highly flexible because of a varying and evolving environment. Therefore real-time process control and, possibly as a result, production optimization are extremely challenging areas. Traditional approaches often do not work due to a lack of robustness or reliability. For this reason, a new generation of decision support systems is needed in response to some specific problems. The thesis addresses topics such as design of intelligent interfaces for knowledge acquisition and elicitation, use of that knowledge for improved data analysis and diagnostics, real-time feedback control, self-tuning capabilities, and evaluation of optimization methods in discrete processes. Topics covered therefore include the whole scope of a decision support system, from its design through to the evaluation of its performance as well as interaction capabilities as a vehicle for sharing information. The aim of this research is to streamline the development of a new generation of decision support systems by providing tools and methods for a better integration of knowledge in an evolving environment. The main interest lies not only in improved data analysis, but also in better formalization and use of diagnosis. Case studies presented in this thesis demonstrate the practical feasibility of such an approach.

Please read the abstract in the section 00front of this document / Dissertation (MCom (Computer Auditing))--University of Pretoria, 2008. / Accounting / MCom / unrestricted

A consumer health decision support system (CDSS) is being developed at the South African Medical Research Council (MRC). It is a software program intended to help members of the public decide when they may be at risk of some common but serious illnesses like tuberculosis and hypertension. It would be ideal for a public health kiosk or e-health programs of the government. The program has been built as an expert system. Its knowledge base consists of rules which are used in assessing the risk of illness. The rules were given by medical experts who took part in the development of the CDSS. The study proposes a method for the evaluation of the rule base of the CDSS using FCA methods. It is important to evaluate the knowledge base of an expert system, because if its knowledge base is of broad scope and is accurate then it can be expected that the expert system will be good at giving advice and hence potentially useful. FCA is a mathematical framework which can be used to investigate causal relations in data. The study explored its utility in the evaluation of the CDSS knowledge base. FCA implications and the FCA formulation of the JSM method were two FCA methods that were selected. The FCA methods were used to generate rules from actual patient data, and these were compared to the rules initially given by the experts. The motivation to use FCA data analysis as well as experts’ knowledge in the development of the CDSS program is that FCA data analysis may discover some things that the experts may have overlooked. Or at least the experts can review their expertise against actual field data which has been analysed by FCA methods. A system like the CDSS cannot be built using FCA data analysis techniques only, involvement of experts is very important. The two FCA methods were chosen so as to compare their results, and it was also thought that they may perhaps complement each other. Preliminarily it was found that FCA implications and the FCA formulation of the JSM method can be used in the evaluation of the rule base of the CDSS. / Dissertation (MSc (Computer Science))--University of Pretoria, 2008. / Computer Science / unrestricted

One of the most significant keys to value creation comes from placing emphasis on producing knowledge. The production of knowledge must a major part of the production strategy. This study aims to harness the concept of knowledge management (KM) as an essential element in the creation of sustainable competitive advantage for organisations. Accordingly, this research seeks to highlight the concept of knowledge management systems (KMS) as an essential element, in which the decision support system (DSS) and organisational performance (OP) are elements that control the survival of organisations in the marketplace. The industry requires creative thinking to generate innovation, learning and excellence in knowledge cognition and knowledge inertia, as well as knowledge acquisition (KA), and spending in three types of DSS: the group decision support system (GDSS), executive support system (ESS) and the expert system (ES). It also requires investment in experience inertia and in work teams for the purpose of access to cross-pollination of the information between the employees and to find new ideas about the industry. This study aims to investigate the issues and factors which affect the utilisation of KM as a tool for effective decision-making (DM).Therefore, decision models and DSSs which enhance effective utilisation of this approach will be investigated. Accordingly, a conceptual model based on the literature review and consultations with knowledge workers was developed. Studies of collaborating organisations which are active in manufacturing in Iraq and the UK were performed to validate the conceptual model and facilitate exploratory investigation regarding the relationships. Data was collected using personal interviews with managers and knowledge workers at the enterprises, in addition to use of the questionnaire which was distributed to samples within these firms. A case study method was used in the data collection stage. These case studies could also be implemented for the mechanical, systems engineering, and manufacturing industries. This is because the findings have been tested where the primary objectives of this study investigate KM gaps in the manufacturing industries generally. This study has also addressed the examined objectives by providing an explanation of several issues, identifying the key sources of KM and the corresponding factors. According to the study, KM is found to occur most strongly over the stages of manufacturing and on which high level KM mainly occurs. Furthermore, this study ties together the concepts of KM, DSS and performance as a way of creating sustinable competitive advantage for the firms. Similarly, the study examines the current use of KM tools and assesses the most prominent methods. This study explores the role of KM in industrial firms and the limitation of obstacles to avoid the gaps. Thus, this study proposes a businesslike framework and creative method, explaining comprehensively how KM must adjust in order to align employees' ideas with the firm's larger goals effectively and strategically, which will reduce the lack of harmonisation between the polarisation and implementation of KMS to those firms. The study identifies high correlation between KM and OP, in addition to identifying high correlation between computer-based DSS and OP.

Call number: LD2668 .T4 1979 F37 / Master of Business Administration

Persistent conflicts between stakeholders and complex trade offs among forest values have created a difficult decision environment for sustainable forest management. Tools developed for decision support in land use planning are essential for managing these challenges. This research study is an interactive assessment of a land use planning Decision Support Tool (DST) in the Invermere Timber Supply Area (TSA), located in the East Kootenay area of British Columbia. The aim of this study is to explore whether stakeholders' initial stated preferences change and whether trade-offs are made between various forest values upon observation of a long-term forecast of these values using a DST. Representatives from various stakeholder groups in the area were assembled for individual sessions to interact with the multi-criteria DST. Participants were required to state their preferences for six forest values using a weighting scheme. The DST developed an output for each forest value based on the participants' preferences. Upon review of the DST output, the participant had the opportunity to alter their initial preferences iteratively until a desirable output was found. The results indicate that participants' preferences changed after reviewing the DST outputs and that participants are willing to make trade-offs between various forest values using a DST to find a desirable solution. However, the preference order of the forest values changed only slightly from the participants' initial to preferred scenarios; instead participants made drastic changes to the weighting of each value to find a desirable output. Participants also stated their willingness to use DSTs for land use planning decision-making, although underlying assumptions built into the model must be improved before stakeholders can trust the tool as an aid for decision-making. Studies such as this can further the development of DSTs to help find desirable decisions for sustainable resource management and to help create a productive and engaging process. / Forestry, Faculty of / Graduate

Statement of the problem: The risk-benefit profile of warfarin anticoagulation in hemodialysis (HD) patients differs compared to the non-HD population. Computerized decision support systems (CDSS) to assist with anticoagulation management are safe and effective in the non-HD population but had not previously been studied in HD outpatients. Methods of investigation: A before – after study compared anticoagulation control during pre-existing, nephrologist-led anticoagulation management to that following implementation of a pharmacist-led, CDSS-assisted strategy, in HD patients on warfarin at The Ottawa Hospital. Results: Forty-two patients were included. Following implementation of the CDSS-assisted strategy, median time-in-range increased by 3.7% (IQR, -9.5% - 20.6%; p = 0.247). Median frequency of INR tests per day decreased: -0.040 (IQR, -0.074 to –0.0008; P = 0.0001). Adverse events were similar. Conclusion: A CDSS-assisted strategy for anticoagulation management in HD patients is effective, safe and may lead to cost savings related to less frequent INR testing.