Data, crucial for decision$-$making, is consistently generated in daily life, shaping our preferences and habits. Businesses harness this information, particularly in understanding customer trends, with the integration of technology giving rise to the concept of "big data." Machine learning $($ML$),$ a subset of artificial intelligence, relies on a robust learning algorithm and quality training data. The common pairing of ML and big data facilitates efficient analysis and the extraction of valuable insights. This collaboration enhances decision$-$making across business domains, including targeted advertising and trend prediction. Nevertheless, ethical concerns, such as privacy issues, biases in data affecting equity, and potential infringement on autonomy when analyzing sensitive information without consent, accompany the integration of big data and ML in decision$-$making processes.