NIT6130 Literature Review: Data Science and Big Data Analysis

This literature review examines the emerging field of data science and big data, focusing on data-driven decision-making processes. The review is structured in three rounds, each exploring relevant keywords and associated research articles. The first round introduces the core concepts of data science, big data, and their impact on decision-making, with keywords like 'analytics' and 'data engineering'. The second round delves into data mining techniques, including classification and clustering, and explores the application of these techniques to the Internet of Things. The third round expands on the previous rounds, exploring the intersection of big data with cloud computing, and delves into deep learning, predictive analysis, and supply chain management. Each round includes a table of research articles, providing titles, authors, years, and journal/conference details, along with summaries of the findings and the identification of new keywords. The review highlights the evolution of research in big data, from initial concepts to advanced applications. The report highlights the importance of data science and big data in various domains and serves as a comprehensive overview of current research trends.