Predictive Analytics for Proactive Product Success Monitoring: A Framework for Real-Time Dashboard Development Using SQL, Tableau, and Snowflake
Abstract
This study presents a comprehensive framework for developing real-time monitoring dashboards that integrate SQL, Tableau, and Snowflake technologies to track system health, customer experience, and product success metrics. The research addresses the critical need for proactive intervention capabilities before service degradation occurs. Through a mixed-methods approach combining literature review, case study analysis, and empirical testing, we developed and validated a predictive analytics framework that enables organizations to monitor product performance indicators in real-time. The findings demonstrate that integrated dashboard solutions can reduce service downtime by 34% and improve customer satisfaction scores by 28% when properly implemented. The study contributes to the growing body of knowledge on predictive analytics applications in product management and provides practical guidelines for implementing proactive monitoring systems.
Keywords
Predictive Analytics, Real-Time Monitoring, Dashboard Development, SQL, Tableau, Snowflake, Product Success Metrics, Proactive Intervention, System Health Monitoring, Customer Experience Analytics
Citations
IRE Journals:
Rui Zhao, Orufa Sindy Ipalimo "Predictive Analytics for Proactive Product Success Monitoring: A Framework for Real-Time Dashboard Development Using SQL, Tableau, and Snowflake" Iconic Research And Engineering Journals Volume 5 Issue 12 2022 Page 547-559
IEEE:
Rui Zhao, Orufa Sindy Ipalimo
"Predictive Analytics for Proactive Product Success Monitoring: A Framework for Real-Time Dashboard Development Using SQL, Tableau, and Snowflake" Iconic Research And Engineering Journals, 5(12)
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