(untitled) (International Journal of Scientific Research in Science and Technology, 2025)
Rampant growth in web data due to increased growth at zetta byte scales driven by various types of online data sources including online commerce websites, social networks, web sensors, business websites, and user communities has given a boost to extracting valuable information with the help of Big Data Analytics (BDA). The key strength of BDA is that it can process large datasets and reveal underlying trends. Optimizing BDA processes, though, is a challenge since it involves combining different data assets to produce actionable insights. This paper explores the BDA process and what it can do through three case studies of leading BDA tool users. The research uncovers four core elements of the BDA framework: system coordination, data sourcing, big data application services, and end-user interaction. Besides, key supporting factors such as data security, privacy, and management act as fundamental functions that complement these elements throughout the information and technology value chain.