Research Proposal: Machine Learning Algorithm in Big Data Analytics

This research proposal explores the application of machine learning algorithms in online big data analytics. The literature review highlights the significance of big data and machine learning, discussing their combined potential for handling large datasets and solving complex problems. It examines the challenges, such as security and network configuration, and proposes solutions like encryption techniques and land utilization approaches. The research methodology outlines the philosophical stance (interpretivism), research approach (inductive), design (mixed methods), strategy (survey and literature review), data collection methods (primary and secondary), sampling procedure (probability), and data analysis techniques (descriptive statistics). The study aims to improve the performance of machine learning techniques in big data environments, addressing issues of data transfer, risk management, and security, and proposes using prediction, clustering, and classification methods to enhance performance. The research will employ a survey through a questionnaire and in-depth literature review for data collection, with a sample of 20 employees, and Ms-Excel software will be used for data analysis.