Now a fundamental component of computer science, data mining has fundamentally altered our ability to extract insights from massive, sophisticated databases. From its early days to the contemporary, AI-driven approaches we know today, and even hint at what might lie ahead, we examined 4285 scientific publications—yes, thousands—in this paper to follow the meandering route of data mining. We found recurring patterns in the development of algorithms, noted how various disciplines adopt similar ideas, and even plotted the sites of research contributions. With big data technologies taking front stage in today's data mining operations, traditional statistical techniques have often given way to machine learning. While we propose that deep learning, automatic machine learning (AutoML), and explainable artificial intelligence (AutoML) may soon take front stage, we also investigate important challenges including scalability, keeping data private, and making outcomes easy to grasp. These findings generally highlight how steadily data mining is influencing data-based decisions in social, commercial, and scientific domains.