3. Electronic Theses and Dissertations (ETDs) - All submissions
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Item A software architecture for a real-time big data system: a case study of a spectrum-sensing enabled whitespace database(2018) Montsi, Litsietsi GeorgeDue to the ever-growing need to process vast amounts of data in real-time, more and more tools which serve different needs in the real-time Big Data processing pipeline have sprung out. However, holistic industry accepted frameworks that address all real-time Big Data processing requirements across the entire pipeline have not yet been developed. More so, the area of dynamic spectrum access, has more and more devices connecting to previously unavailable radio frequency spectrum. This vastly growing number of devices need real-time orchestration on how they access this newly made available spectrum. The development of a real-time Big Data system in the realm of dynamic spectrum access as required by the Council for Scientific and Industrial Research served as a case study for this research. This research provides a step in reaching an industry wide accepted software reference architecture which will be followed in the development of real-time Big Data systems. This is done through uncovering the most important quality/architectural requirements of realtime Big Data systems which such a reference architecture is to address. It is shown that all major software reference architectures (Java Enterprise Edition, AutoSar, Microsoft.Net, and others) were developed with emphasis placed on addressing a set of specific prioritised requirements. Hence this research uses this principle to propose a method to help in the development of software architectures and software reference architectures of real-time Big Data systems. In this research, a case study is used to make inference on the general population of real time Big Data systems about the method proposed in this research. A mathematical ranking method is employed to prioritise software architecture requirements of a case study system and the results are compared with literature to increase the accuracy of the inference. Then architecture design and experiments were carried-out and presented to the Council for Scientific and Industrial Research as the client for acceptance, which would serve as validation. This was further validated by comparing the results of the case study to work done by other researchers. Having uncovered the most important quality attributes for realtime Big Data systems, the software architecture design process for such systems is simplified and fertile ground has been laid for the development of software reference architectures for real-time Big Data systems.Item Data scientist : using a competency based approach to explore an emerging role(2018) Nosarka, Naseema BanuPurpose: The aim in this research study was to explore the role and competencies of Data Scientists in South Africa as the role starts to emerge. Due to the newness of the role, jobs in this sphere are currently being filled by skilled professionals moving from other related areas. Knowledge and skills for Data Scientists were explored in order to examine the role of a Data Scientist and the competencies they should have. Design/methodology/approach: The studies that have been published on the role of a Data Scientist are limited as the field of Data Science is still new. Therefore the design of the research was exploratory and used qualitative methods. Data gathered for this research was analysed using thematic analysis. The study used respondents drawn from the banking and insurance industries as they are amongst the first to employ Data Scientists in the real sense of the term in South Africa. Six Data Scientists were interviewed. Originality/value: Research that focuses on the role of Data Scientists especially in South Africa is limited as most of the research has taken place in developed countries. There is also limited research on the role of a Data Scientist within the banking and insurance industry. This study contributes to practitioner and research knowledge by exploring the emerging role of a Data Scientist in the South African context. Practical implications: This research improves our understanding of the knowledge and skills Data Scientists should have within the banking and insurance industry. This research adds insight by highlighting the role that Data Scientists are currently undertaking by providing information on the specific skills that they report as required. This research can help in the shaping of education and developing the required skills for individuals who intend to pursue the career path of a Data Scientist as well as help managers hire the right people for the position of a Data Scientist.Item Virtual wind sensors: improving wind forecasting using big data analytics(2016) Gray, Kevin AlanWind sensors provide very accurate measurements, however it is not feasible to have a network of wind sensors large enough to provide these accurate readings everywhere. A “virtual” wind sensor uses existing weather forecasts, as well as historical weather station data to predict what readings a regular wind sensor would provide. This study attempts to develop a method using Big Data Analytics to predict wind readings for use in “virtual” wind sensors. The study uses Random Forests and linear regression to estimate wind direction and magnitude using various transformations of a Digital Elevation Model, as well as data from the European Centre for Medium-Range Weather Forecasts. The model is evaluated based on its accuracy when compared to existing high resolution weather station data, to show a slight improvement in the estimation of wind direction and magnitude over the forecast data.