126
Kumar, Y., Marchena, J., Awlla, A.H., Li, J.J., & Abdalla, H.B. (2024). The AI-Powered
Evolution of Big Data. Applied Sciences, 14(22), 10176.
hps://doi.org/10.3390/app142210176
Lim, W.M. (2024). What Is Quantitative Research? An Overview and
Guidelines. Australasian Marketing
Journal, 0(0). hps://doi.org/10.1177/14413582241264622
Mahadevkar, S.V., Patil, S., Kotecha, K. et al. (2024). Exploring AI-driven approaches
for unstructured document analysis and future horizons. J Big Data, 11(92).
hps://doi.org/10.1186/s40537-024-00948-z
Makin, T.R., & Orban de Xivry, J.J. (2019). Ten common statistical mistakes to watch
out for when writing or reviewing a manuscript. eLife, 8, e48175.
hps://doi.org/10.7554/eLife.48175
Miles, M.B., Huberman, A.M., & Saldaña, J. (2014). Qualitative data analysis: a methods
sourcebook. London: SAGE Publications, Inc
Miller, T., Durlik, I., Łobodzińska, A., Dorobczyński, L., & Jasionowski, R. (2024). AI in
Context: Harnessing Domain Knowledge for Smarter Machine Learning. Applied
Sciences, 14(24), 11612. hps://doi.org/10.3390/app142411612
Mishra, P., Pandey, C.M., Singh, U., Keshri, A., & Sabaretnam, M. (2019). Selection of
appropriate statistical methods for data analysis. Annals of cardiac anaesthesia, 22(3),
297–301. hps://doi.org/10.4103/aca.ACA_248_18
Naomi, C., Adebimpe, B., Victor, I.A., & Osemeike, G.E. (2024). Frameworks for
eective data governance: best practices, arguments, and implementation strategies
across industries. Computer Science & IT Research Journal, 5(7), 1666-1679.
hps://doi.org/10.51594/csitrj.v5i7.1351
Noyes, J., Booth, A., Moore, G., Flemming, K., Tunçalp, Ö., & Shakibazadeh, E. (2019).
Synthesising quantitative and qualitative evidence to inform guidelines on complex