The Internet of Things has emerged as an evolving paradigm and has developed its presence in a variety of domains around us. The emergence of IoT has also emphasized the need to cater to challenges such as interoperability, smart IoT components adoption, authentication and authorization, networking, information retrieval, and several other issues. The ubiquitous nature and interconnection between various devices supported by machine learning, artificial intelligence, cloud computing, big data, and blockchain lead to a generation of large amounts of data. In order to find useful information from such data is a tedious task and involves high computation. The domain of Information Retrieval helps us to identify and manage environmental factors of data collected through sensors. The data gathered may be heterogeneous and from different sources. This demands the need for better retrieval efficiency, accuracy, and systematic models for gathering and managing the sensed data. Designing such a model with security and privacy is a major concern. The acquired knowledge from those models will be helpful for data analytics, performance-boosting, decision making, and managing the resources efficiently. A detailed study of the importance of Information Retrieval and Data Analytics in the Internet of Things is presented in this paper.