Population growth and the fast pace of urbanization have accelerated the problem of conventional waste management systems. Data analytics-based Smart Waste Management Systems (SWMS) are the future solution to maximize waste collection, recycling, and resource usage. As the world's population increases and urbanization increases, cities frequently find it difficult to offer sustainable, safe, and convenient lifestyles because they lack the smart technologies that are required [4]. By leveraging real-time data and advanced analytics, cities can achieve more efficient traffic management, reduce energy consumption, streamline waste collection, and enhance emergency response systems [1]. There is a widespread practice in all developing nations to dump trash on the streets and in public spaces, which primarily harms the environment and leads to a number of unsanitary issues [9]. This paper describes the use of data analytics in smart waste management, its use in the optimization of resource usage, and the future effects of such systems on urban waste management