• Sushma Kukkadapu

This research presents a novel approach to real-time business intelligence dashboards for financial decision-making in large enterprise environments. By reimagining the traditional extract-transform-load (ETL) pipeline through strategic automation and intelligent caching mechanisms, this system significantly reduces data latency while maintaining accuracy in financial visualizations. Implementation testing across multiple retail use cases demonstrated a 78% reduction in dashboard refresh time (from an average of 42 minutes to 9.2 minutes) and a 64% decrease in computational resource utilization compared to traditional BI approaches. The system achieves these improvements through a microservices architecture with specialized components for data source monitoring, differential data extraction, parallel transformation processes, and intelligent data materialization. This research contributes a practical, implementable approach to near-real-time financial intelligence that enables more responsive decision-making while operating within existing enterprise infrastructure constraints.

Business Intelligence, Financial Dashboards, ETL Pipeline, Data Visualization, Enterprise Systems, Real-time Analytics, Microservices Architecture, Data Materialization.

"Real-Time Business Intelligence Dashboard For Financial Decision-Making: A Streamlined Data Pipeline Approach", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 4, page no.n35-n42, April-2025, Available :http://www.jetir.org/papers/JETIR2504D06.pdf

"Real-Time Business Intelligence Dashboard For Financial Decision-Making: A Streamlined Data Pipeline Approach", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 4, page no. ppn35-n42, April-2025, Available at : http://www.jetir.org/papers/JETIR2504D06.pdf