Big Data Research: An Annotated Bibliography of Key Resources

This annotated bibliography provides a compilation of key resources related to big data technologies and analytics. It includes summaries of books and journal articles covering various aspects of big data, such as technologies, challenges, impacts on organizational performance, effectiveness in different sectors like tourism, and characteristics. The bibliography also highlights research on big data quality assessment models, the effect of mobile advertising platforms, and the role of big data analytics in marketing and operations management. Each entry offers a brief overview of the resource's content, making it a useful tool for researchers and students seeking to understand the multifaceted field of big data.

Academic Misconduct
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Table of Contents
REFERENCES................................................................................................................................3
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REFERENCES
Books and journals
1. Oussous, A., Benjelloun, F.Z., Lahcen, A.A. and Belfkih, S., 2018. Big Data technologies: A
survey. Journal of King Saud University-Computer and Information Sciences. 30(4).
pp.431-448.
From this book, strategies like detecting outliers and others have been taken regarding
managing big data.
2. Hariri, R.H., Fredericks, E.M. and Bowers, K.M., 2019. Uncertainty in big data analytics:
survey, opportunities, and challenges. Journal of Big Data. 6(1), pp.1-16.
Content that has been taken from this journal include: challenges and impacts of big data
on organisations' performance.
3. Ge, M., Bangui, H. and Buhnova, B., 2018. Big data for internet of things: a survey.
Future generation computer systems. 87. pp.601-614.
Content that has been selected from this book include: effectiveness of big data in this
digital world.
4. Li, J., Xu, L., Tang, L., Wang, S. and Li, L., 2018. Big data in tourism research: A literature
review. Tourism Management. 68. pp.301-323.
From this book, effectiveness of big data in tourism sector has been known for knowing
ways of managing big data.
5. Choi, T.M., Wallace, S.W. and Wang, Y., 2018. Big data analytics in operations
management. Production and Operations Management. 27(10). pp.1868-1883.
From this book, impacts of big data has been selected in operational management.
6. Sun, Z., Strang, K. and Li, R., 2018, October. Big data with ten big characteristics. In
Proceedings of the 2nd International Conference on Big Data Research (pp. 56-61).
Some main big characteristics of big data have been discussed from this journal.
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7. Younas, M., 2019. Research challenges of big data.
Some challenges that companies face regarding managing big data has been taken from
this journal.
8. Silva, B.N., Diyan, M. and Han, K., 2019. Big data analytics. In Deep Learning:
Convergence to Big Data Analytics (pp. 13-30). Springer, Singapore.
Content that has been taken from this book is: popularity and reasons of companies to use
big data analytics.
9. Taleb, I., Serhani, M.A. and Dssouli, R., 2018, November. Big data quality assessment
model for unstructured data. In 2018 International Conference on Innovations in
Information Technology (IIT) (pp. 69-74). IEEE.
Some models and theories have been discussed from this book,
10. Bae, S.D. and Park, D.H., 2018. The Effect of Mobile Advertising Platform through Big
Data Analytics: Focusing on Advertising, and Media Characteristics. Journal of
Intelligence and Information Systems, 24(2), pp.37-57.
It has discussed roles as well as impacts of big data analytics on different functions of
companies such as marketing and others.
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