CAWAL: A novel unified analytics framework for enterprise web applications and multi-server environments

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Authors Γ–zkan Canay, Ümit KocabΔ±Γ§ak arXiv ID 2503.23244 Category cs.HC: Human-Computer Interaction Cross-listed cs.DC, cs.IR Citations 5 Venue Information Processing & Management Last Checked 4 months ago
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.
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