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Exploring the potential of big data and data analytics in South Africa's real estate sector

Author/s: Koech Cheruiyot, Lungile Gamede

Date Published: 8/03/2025

Published in: Volume 29 - 2024 Issue 3 (pages 66 - 78)

Abstract

This paper examines the current applications, barriers, and potential uses of big data and data analytics in the South African real estate market. A qualitative approach was adopted to administer semi-structured interviews to big data and data analytics specialists in the South African real estate market. The results show that the proptech market is still in its infancy in general and that the big data and data analytics submarket is limited in the South African real estate market. Major challenges include the lack of clarity or knowledge of adequate value proposition related to upscaling, supportive ecosystem, storage systems, costs, and the scarcity of technical skills needed for big data and data analytics to blossom. Besides these issues, anecdotal evidence, showing the presence of active companies focusing on big data, and responses from research participants, suggest that big data and big data analytics can grow and potentially bring immense benefits to all stakeholders in the country.

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Keywords

Big Data - Big Data Analytics - Proptech - Real Estate Market - South Africa

References

  • Akter, S and Wamba, S.F., (2016). Big data analytics in E-commerce: a systematic review and agenda for future research. Electronic Markets, 26, pp.173-194.
  • Alharthi, A., Krotov, V. and Bowman, M., 2017. Addressing barriers to big data. Business Horizons, 60(3), pp. 285-292.8), pp.6112-6130.
  • Clark, P. (2024). Personal communication, January 22.
  • Clark, P. &
Marshall, M. (2023). Proptech: Shaping the future of the South African property market through technology. South African Property Owners Association, Johannesburg, South Africa.
  • Creswell, J. W., & Creswell, J. (2018). Research design: Quantitative and qualitative approaches (5 ed.). Thousand Oaks, CA: Sage Publications.
  • Davenport, T., & Dych, J. (2013). Big data in big companies. International Institute for Analytics, 3, 1-31.
  • Dworkin, S. L. (2012). Sample size policy for qualitative studies using in-depth interviews. Archives of Sexual Behavior, 41(6), pp. 1319–1320.
  • Du, D., Li, A., & Zhang, L. (2014). Survey on the applications of big data in Chinese real estate enterprise. Procedia Computer Science(30), 24-33.
  • Fetch Analytics (2024) What can Fetch do for you, Retrieved from: https://fetchanalytics.ai/January 20.
  • Godoy, S., & Boyle, L. (2019). Unpacking the Current & Future Impact of Technology on the South
  • African Property Industry: Identifying Key Features of the Proptech Ecosystem. UCTNedbank Urban Real Estate Research Unit and contributors. Retrieved from
  • http://www.ureru.uct.ac.za/
  • Guest, G., Bunce, A. and Johnson, L., (2006). How many interviews are enough? An
  • experiment with data saturation and variability. Field methods, 18(1), 59-82
  • Herman, D., Kent, E., & Michael, S. (2018). Digital Cities: Real Estate Development Driven by Big
  • Data. Stanford: Global Projects Centre.
  • Kamilaris, A., Kartakoullis, A. and Prenafeta-Bold, F.X., 2017. A review on the practice of big
  • data analysis in agriculture. Computers and electronics in agriculture, 143, pp.23-37.
  • Kitchin, R., & McArdle, G. (2016). What makes Big Data, Big Data? Exploring the ontological
  • characteristics of 26 datasets. Big Data & Society, 3(1).
  • Koscielniak, H., & Puto, A. (2015). Big data in decision-making processes of enterprises.
  • Procedia Comput Sci, 1052-1058.
  • Luo, J., Wu, M., Gopukumar, D. and Zhao, Y., 2016. Big data application in biomedical
  • research and health care: a literature review. Biomedical informatics insights, 8, pp.BIIS31559
  • Lightstone. (2022). Lightstone. Retrieved from Lightsttone: https://lightstone.co.za/AboutLMP.
  • (2024). Digital revolution: How technology is reshaping South African real estate,
  • Retrieved from: https://www.lwp.co.za/news/digital-revolution-how-technology-isreshaping-south-african-realstate/#:~:text=Analysing%20vast%20amounts%20of%20data,shifts%20and%20make%
  • 20informed%20decisions.
  • Madden, S. (2012). From databases to big data. IEEE Internet Computing, 4-6.
  • Marshall, B., Cardon, P., Poddar, A., & Fontenot, R. (2013). Does sample size matter in
  • qualitative research? A review of qualitative interviews in is research. Journal of
  • Computer Information Systems, 54(1), pp. 11–22
  • Michael K, & Miller, K.W. (2013). Big data: New opportunities and new challenges. Computer,
  • 46(6), 22-24.
  • Mohanty, S., Jagadeesh, M., & Srivatsa, H. (2013). Big data Imperatives: Enterprise “big data”
  • Warehouse, implementations, and Analytics, Apress: New York, USA.
  • Neilson, A., Daniel, B. and Tjandra, S., 2019. Systematic review of the literature on big data in
  • the transportation domain: Concepts and applications. Big Data Research, 17, pp.35-44.
  • Oluwunmi, A., Role, B., Akinwale, O., Oladayo, O., & Afolabi, T. (2019). Big Data and Real
  • Estate: A Review of Literature. Journal of Physics: Conference Series, 1378(3), 032015.
  • Nobanee, H., Dilshad, M.N., Al Dhanhani, M., Al Neyadi, M., Al Qubaisi, S. and Al Shamsi,
  • S., 2021. Big Data applications the banking sector: A bibliometric analysis
  • approach. Sage Open, 11(4), p.21582440211067234.
  • Onay, C. and Ã, E., 2018. A review of credit scoring research in the age of Big
  • Data. Journal of Financial Regulation and Compliance, 26(3), pp.382-405.
  • Pejić
    • Bach, M., Krstić, Seljan, S. and Turulja, L., 2019. Text mining for big data analysis in financial sector: A literature review. Sustainability, 11(5), p.1277. Pettit, C., Liu, E., Rennie, E., Goldenfein, J., & Glackin, S. (2018). Understanding the disruptive technology ecosystem in Australian urban and housing contexts: a roadmap. Pyle, A., Grunewald, D., & Wright, N. (2017). Bridging the gap. How the real estate sector can engage with PropTech to bring the built and digital environments together. Retrieved from https://assets.kpmg.com/content/dam/kpmg/uk/pdf/2017/-11/proptech-br Ridge, M., Johnston, K. and O'Donovan, B. (2015). The use of big data analytics in the retail industries in South Africa. African Journal of Business Management, 9(19), 688-703. Snow, W. (2013) Ascendix’s Wes Snow on which Proptech trends will bring returns in 2023. https://www.propertyweek.com/comment/ascendixs-wes-snow-on-which-proptechtrends-will-bring-returns-in-2023/5124201.article Sun, G., Liang, R., Wu, F., & Qu, H. (2013). A web-based analytics system for real estate data. Information Sciences, 5(56), 154-166. Thakuriah, P., Tilahun, N., & Zellner, M. (2017). Big Data and Urban Informatics: Innovations and Challenges to Urban Planning and Knowledge Discovery. In P. Thakuriah, N. Tilahun, & M. Zellner (Eds.), Seeing Cities through Big Data: Research, Methods, and Applications in Urban Informatics (pp. 11-48). Springer NY. TPN. (2022). TPN. Retrieved from https://www.tpn.co.za/group Ullah, F. and Babar, M.A., 2019. Architectural tactics for big data cybersecurity analytics systems: a review. Journal of Systems and Software, 151, pp.81-118. Vistro, D.M., Rehman, A.U., Mehmood, S., Idrees, M. and Munawar, A., 2020. A literature review on security issues in cloud computing: Opportunities and challenges. Journal of Critical Reviews, 7(10), pp.1446-1455. Winson-Geideman, K., & Krause, A. (2016). Transformations in Real Estate Research: The Big Data Revolution. 22nd Annual Pacific-Rim Real Estate Society Conference. Sunshine Coast, Queensland, Australia. );