Developing business intelligence application by using machine learning techniques in real estate sector

With the developments in information and communication technologies, the needs of enterprises to interpret their data are increasing day by day. In this context, it is important for enterprises to manage this continuously flowing and increasing data effectively. This situation necessitates enterprises to adapt their business processes to new technologies. In this sense, business intelligence applications are one of the most used solutions in recent years. Businesses that had to analyze and interpret this big data began to integrate techniques such as machine learning into their specific operations. Especially the dynamic and wide data structure of the real estate sector has brought about the use of effective and advanced reporting tools. This study proposes a new generation technological approach used to achieve effective analysis results in the real estate sector. The aim of this work is to provide information to banks, credit financing institutions, construction companies, intermediaries, valuation experts and consultants; to provide information such as real estate prices and indices, valuation module, macro-economic data and trend analysis, to closely monitor the market, to identify sector opportunities and to develop a business intelligence application for operational, tactical and strategic decisions. Software and frameworks used for designing Business Intelligence Application: PHP, Python and Flask.