CAWAL: A novel unified analytics framework for enterprise web applications and multi-server environments
arXiv:2503.23244 · doi:10.1016/j.ipm.2023.103617
Abstract
In web analytics, cloud-based solutions have limitations in data ownership and privacy, whereas client-side user tracking tools face challenges such as data accuracy and a lack of server-side metrics. This paper presents the Combined Analytics and Web Application Log (CAWAL) framework as an alternative model and an on-premises framework, offering web analytics with application logging integration. CAWAL enables precise data collection and cross-domain tracking in web farms while complying with data ownership and privacy regulations. The framework also improves software diagnostics and troubleshooting by incorporating application-specific data into analytical processes. Integrated into an enterprise-grade web application, CAWAL has demonstrated superior performance, achieving approximately 24% and 85% lower response times compared to Open Web Analytics (OWA) and Matomo, respectively. The empirical evaluation demonstrates that the framework eliminates certain limitations in existing tools and provides a robust data infrastructure for enhanced web analytics.
This is a preprint version of a research article printed in journal. The manuscript includes 21 pages, 10 figures, and 3 tables