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Fragmented Data Landscape and Data Asymmetries in the Real Estate Industry

In: Blockchain in Real Estate

Author

Listed:
  • Hamad Hazeem

    (Real Estate Regulatory Authority (RERA))

  • Ebrahim AlBurshaid

    (Real Estate Regulatory Authority (RERA))

Abstract

This chapter explores the challenges posed by fragmented data in the real estate industry and its impact on transactions. Fragmented data refers to the scattered and disjointed nature of information within the industry, hindering decision-making and impeding transactions. The presence of data asymmetries further exacerbates these challenges, creating an imbalance of power and a lack of transparency. To address these issues, the industry is witnessing trends toward data standardization and centralization, aiming to establish unified data frameworks and repositories. Leveraging technology, such as artificial intelligence and machine learning, is crucial in overcoming data fragmentation by processing vast amounts of data, extracting insights, and streamlining processes. Additionally, blockchain technology offers a promising solution by providing a decentralized and secure ledger for real estate data, eliminating intermediaries, and enhancing trust. Real-world examples of successful blockchain applications in real estate demonstrate its transformative power. The integration of fragmented data holds immense potential for transforming the real estate landscape, unlocking new opportunities, improving decision-making, and creating a transparent and efficient ecosystem. The continued use of artificial intelligence, machine learning, and blockchain will play pivotal roles in shaping the future of real estate data integration.

Suggested Citation

  • Hamad Hazeem & Ebrahim AlBurshaid, 2024. "Fragmented Data Landscape and Data Asymmetries in the Real Estate Industry," Springer Books, in: Ammar Jreisat & Mehdi Mili (ed.), Blockchain in Real Estate, pages 179-205, Springer.
    • Handle: RePEc:spr:sprchp:978-981-99-8533-3_10
    DOI: 10.1007/978-981-99-8533-3_10
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