CAWAL: A novel unified analytics framework for enterprise web applications and multi-server environments
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arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866916666110115840 |
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| author | Canay, Özkan Kocabıçak, Ümit |
| author_facet | Canay, Özkan Kocabıçak, Ümit |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_23244 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | CAWAL: A novel unified analytics framework for enterprise web applications and multi-server environments Canay, Özkan Kocabıçak, Ümit Human-Computer Interaction Distributed, Parallel, and Cluster Computing Information Retrieval 68T09, 68M14, 68P20, 68N01, 68U35 H.3.5; H.2.8; D.2.8; C.2.4; K.6.5 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. |
| title | CAWAL: A novel unified analytics framework for enterprise web applications and multi-server environments |
| topic | Human-Computer Interaction Distributed, Parallel, and Cluster Computing Information Retrieval 68T09, 68M14, 68P20, 68N01, 68U35 H.3.5; H.2.8; D.2.8; C.2.4; K.6.5 |
| url | https://arxiv.org/abs/2503.23244 |