Avaliação de preços e vendas no setor imobiliário utilizando o Big Data

Abstract

Organizational decisions have been guided by data analyzes, which gain more relevance each day. Interest in Big Data grows as the companies applying Big Data deliver significant results. In this context, it is vital to take advantage of the opportunities arising from data analysis. Some of the benefits to the real estate industry are the ability to identify trends and patterns of buying and selling, this trends have helped develop more effective selling strategies. For this, the objective of this work was to analyze which factors influence the prices and volumes of real estate sales and how to obtain an equation that models the functioning of these phenomena. The approach adopted to carry out the modeling proposed in this work was based on the analysis of multiple linear regression. As main results, it was found that the models generated for sales price forecasts presented dispersions in relation to real market values varying from 2% to 11%. The models for sales volume forecasts presented perfect adjustments in relation to market behavior. As conclusions, it was found that the use of Big Data in the real estate market reduces the risks in the decision-making process for the developers in relation to the launch of new ventures