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Future Trends in Web Analytics: A Comprehensive Review

Valentin Kuleto, Mladen Radaković

Abstract


This review paper explores future trends in web analytics, focusing on their impact on business and technological advancements. The paper discusses critical areas such as advanced data analytics, mobile analytics, offline and online data integration, privacy protection, and data visualisation. Drawing upon scientific literature, the paper highlights the significance of artificial intelligence, machine learning, and sentiment analysis in deepening data insights. Integrating offline and online data and the growing importance of mobile analytics offer valuable opportunities for businesses to optimise user experience. The ethical considerations surrounding privacy protection and the need for transparent data practices are emphasised. Finally, the paper underscores the importance of data visualisation in enhancing data comprehension and decision-making processes.


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References


Feldman, S. ([). Mobile Analytics: Understanding the Mobile User Experience. O'Reilly Media.

Harrison, L., & Pelletier, C. (2018). Data Visualization: A Practical Introduction. Princeton University Press.

Mittelstadt, B. D., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (2016). The ethics of algorithms: Mapping the debate. Big Data & Society, 3(2), 2053951716679679.

Provost, F., & Fawcett, T. (2013). Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking. O'Reilly Media.

Tuffield, M., Rao, N., & Shmueli, G. (2019). Data Science in Practice: Building Models from Big Data. CRC Press.

Soni, A., Kumar, V., Jain, P. K., & Kumar, U. (2017). Artificial Intelligence in Construction Management. MDPI

Iyer, K. C., Chaphalkar, N. B., & Joshi, G. A. (2012). Understanding time delay disputes in construction contracts. International Journal of Project Management, 30(2), 282-295. HRMARS

Vardeva, I. (2022.). Generalised Net Model of an Automated System for Monitoring, Analysing and Managing Events Related to Information Security. Retrieved from https://dx.doi.org/10.11610/isij.4319

Zhang, L., & Zhang, Y. (2022). Progressive Visualization of Earthquake Big Data Based on Cloudberry. Journal of Computers, 33(1), 1–14. Retrieved from https://doi.org/10.53106/199115992022023301009

Sharma, S. (2023, April 19). The Future of Web Analytics: Emerging Trends and Technologies to Watch. Growth Natives. https://growthnatives.com/blogs/analytics/the-future-of-web-analytics/

Heesen, P., Studer, G., Bode, B., Windegger, H., Staeheli, B., Aliu, P., Martín-Broto, J., Gronchi, A., Blay, J., Le Cesne, A., & Fuchs, B. (2022). Quality of Sarcoma Care: Longitudinal Real-Time Assessment and Evidence Analytics of Quality Indicators. Cancers. Retrieved from https://dx.doi.org/10.3390/cancers15010047

Carley, R., Fuller, S., Bond, W., Jones, P., Allen, D., Jordan, A., & Falls, T. (2022). Data Analytics and Visualisation Application for Asset Health Monitoring. PHM Society. Retrieved from https://dx.doi.org/10.36001/phmconf.2022.v14i1.3214

Hasnine, M. N., Nguyen, H. T., Tran, T., Bui, H. T. T., Akçapınar, G., & Ueda, H. (2023). A Real-Time Learning Analytics Dashboard for Automatic Detection of Online Learners’ Affective States. Sensors. Retrieved from https://dx.doi.org/10.3390/s23094243

Chaffai, A., Hassouni, L., & Anoun, H. (2017). Real-Time Analysis of Students’ Activities on an E-Learning Platform Based on Apache Spark. International Journal of Advanced Computer Science and Applications. Retrieved from https://dx.doi.org/10.14569/IJACSA.2017.080715




DOI: https://doi.org/10.37628/ijtet.v9i1.1858

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