The tourism sector is extremely competitive and characterized by fierce competition for the discretionary spending of tourists. To effectively compete in the tourism sector, a nation or region must be able to make informed strategic and operational decisions. In this decision-making process, the capacity to predict tourism demand with accuracy in the context of an ever-changing environment may be very helpful. Academic study on tourism is increasingly becoming the main topic as its economic significance increases. Research in this field aids in comparing best practices and spotting new patterns in tourist demand and supply. This is where the exploding use of Big Data in the recent year comes in. Big Data, a relatively newer phenomenon is a complex and huge data set that is derived from a combination of numerous individual data. The main objective of the research is to understand and review the existing research on the application of operation research and big data in the tourism sector for revenue and efficiency maximization, extrapolating data to estimate potential future demand, challenges faced by the hospitality sector, and comprehend the latest trends in tourism marketing, among other things. The paper evaluates the available studies on the tourist business sector using various software available.