https://iaeme.com/Home/journal/IJARET 288 editor@iaeme.com International Journal of Advanced Research in Engineering and Technology (IJARET) Volume 15, Issue 3, May-June, 2024, pp. 288-297, Article ID: IJARET_15_03_025 Available online at https://iaeme.com/Home/issue/IJARET?Volume=15&Issue=3 ISSN Print: 0976-6480 and ISSN Online: 0976-6499 DOI: https://doi.org/10.17605/OSF.IO/MZCN7 Impact Factor (2024): 11.76 (Based on Google Scholar Citation) © IAEME Publication OPTIMIZING QUERY PERFORMANCE IN CLOUD DATA WAREHOUSES: A FRAMEWORK FOR IDENTIFYING AND ADDRESSING PERFORMANCE BOTTLENECKS Sadha Shiva Reddy Chilukoori Meta Platforms Inc., USA Shashikanth Gangarapu Qualcomm Inc., USA Chaitanya Kumar Kadiyala Arm Inc., USA ABSTRACT Cloud data warehouses have become increasingly popular due to their scalability, flexibility, and cost-effectiveness. However, optimizing query performance in such environments can be challenging. This research paper presents a framework for identifying performance bottlenecks and implementing targeted optimizations in cloud data warehouses. The proposed framework considers various factors that influence query execution time, including data partitioning, indexing strategies, and query optimization algorithms. A case study is conducted to demonstrate the effectiveness of the framework in improving query performance in a real-world cloud data warehouse environment. According to the findings, applying the suggested optimizations can cut query execution time by up to 45% while also improving resource utilization by 30%. The findings of this research can help organizations enhance the performance of their cloud data warehouses and make informed decisions regarding optimization strategies. Keywords: Data Partitioning, Indexing Strategies, Query Optimization Algorithms, Performance Monitoring, Resource Utilization Cite this Article: Sadha Shiva Reddy Chilukoori, Shashikanth Gangarapu, Chaitanya Kumar Kadiyala, Optimizing Query Performance in Cloud Data Warehouses: A Framework for Identifying and Addressing Performance Bottlenecks, International Journal of Advanced Research in Engineering and Technology (IJARET), 15(3), 2024, pp. 288-297. https://iaeme.com/MasterAdmin/Journal_uploads/IJARET/VOLUME_15_ISSUE_3/IJARET_15_03_025.pdf