In numerous Internet of Things contexts, there is an increasing interest to use wireless sensor technologies. One of the most difficult problems is gathering and analyzing commodity data, given the enormous rise of smart objects and their applications. Sensor nodes are battery-powered, and energy-efficient operations are important. To that end, before transmitting the final data to the central station, remove redundancy from the collected data by neighbouring nodes is beneficial for sensors. Data aggregation is one of the main strategies for reducing data redundancy and improving energy efficiency; it also extends the lifetime of wireless sensor networks. Moreover, network traffic can be minimized by an efficient data aggregation protocol. It may be sensed by more than one sensor when a particular target takes place in a particular area. This article provides an overview of different data aggregation methods and protocols, taking into account the key problems and facets of data aggregation in wireless sensor networks. The structures of data aggregation are grouped into four key classes, namely cluster-based, tree-based, chain-based and grid-based. The thorough comparison of the important approaches of each class often gives a suggestion for more research.