Analysis of Big Data Application in Real Estate Investment

Abstract

As an important project of national economic growth, real estate plays an important role in education, scientific research and production industries. Despite the slower pace of urbanization, However, the development of real estate has started to slow down currently, and there have been problems such as market differentiation and changes in consumer demand. At the same time, many investors' investments are blindly aimed at adapting to the market, which can easily lead to losses. With the development of the information age, big data can process massive amounts of information and provide investors with effective reference when investing in real estate, thereby improving the efficiency and gold content of real estate investment. This study will describe the application of big data in real estate investment from four aspects: information mining system, housing price evaluation, risk profile and marketing. The information mining system is mainly used in the initial stage of development to provide decision-makers with the preferences of the target customer group. House price prediction and risk prediction are mainly based on BP neural networks. Marketing mainly describes the application of big data in real estate sales. These results demonstrate how big data can help investors better choose investment objects, save investment costs and better meet market demand in the current market environment.