Background of the Study
Big data analytics involves the process of examining large volumes of data to uncover patterns, correlations, and insights that can inform decision-making. In the real estate industry, big data analytics is increasingly being used to predict market trends, assess property values, and optimize investment strategies (Ojo & Alabi, 2024). The use of big data allows real estate professionals to make data-driven predictions about property prices, rental demand, and other key factors that influence the property market. This is especially important in emerging markets where property trends may not always be straightforward and can be influenced by a multitude of social, economic, and environmental factors (Sanni et al., 2023).
Bauchi State, located in northeastern Nigeria, is experiencing significant demographic and economic growth, creating opportunities and challenges for the real estate sector. As the state urbanizes and more people migrate to its cities, property demand is increasing. However, this rapid growth has made it difficult for real estate professionals to accurately predict market trends and make informed investment decisions. Big data analytics offers a solution by providing insights into market dynamics based on historical data, demographic trends, and socio-economic factors (Jibrin et al., 2023). This technology can also help predict shifts in property values, rental prices, and demand patterns, thus providing a competitive edge to real estate investors, developers, and policymakers.
Despite the potential of big data analytics, the adoption of these technologies in Bauchi’s real estate sector has been slow. Many real estate professionals lack the technical know-how to harness big data, and the infrastructure necessary to collect and analyze large datasets is often lacking. Furthermore, concerns regarding data privacy and the reliability of predictions based on big data may hinder its widespread adoption in the region. This study aims to investigate how big data analytics can be used to predict property market trends in Bauchi State, with a focus on understanding the barriers and benefits associated with its use.
Statement of the Problem
Although big data analytics has proven effective in predicting property market trends in more developed regions, its application in Bauchi State remains underexplored. The problem lies in the limited use of big data in the real estate sector, leading to suboptimal decision-making by developers, investors, and policymakers. Without the proper tools and understanding, real estate professionals in Bauchi may struggle to keep pace with market trends, potentially missing investment opportunities or making poor decisions based on outdated or incomplete information.
Furthermore, challenges such as data availability, the need for specialized skills, and infrastructure limitations hinder the full implementation of big data analytics in Bauchi’s real estate market. This study aims to explore how big data analytics can contribute to predicting property market trends in Bauchi and to identify the challenges and opportunities involved in its application.
Objectives of the Study
Research Questions
Research Hypotheses
Scope and Limitations of the Study
This study will focus on real estate professionals in Bauchi State, including developers, investors, and agents, who are involved in property market forecasting. It will explore the use of big data analytics tools, focusing on trends in residential and commercial properties. Limitations include the availability of big data resources and the willingness of participants to share information about their use of these technologies.
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