The goal of utilizing big data in machine learning is to overcome the challenges of processing sizable databases, especially for those containing billions of queries on the entire internet or the activities of every social media user. It is generally cost-effective to develop machine learning algorithms to work with said data for both research and commercial purposes. Machine learning ensures data extraction programs are automated, giving them the ability to learn and adapt based on previous experiences. Those decision-making algorithms evolve through completing assigned tasks and collect deeper insights on datasets for enhancing business operations. Machine learning tools remain particularly valuable, recognizing patterns from data generated and translating them into key performance indicators. That allows statistical models to get applied to business decision-making. A great example would be notifying manufacturers of defective vehicle parts during car testing.