The exponential rise of data—projected to reach 163 zettabytes by 2025—has made big data analytics a cornerstone for decision-making in sectors like healthcare, finance, and retail. Cloud computing enhances this by providing scalable, cost-effective infrastructure to process vast, diverse datasets. This paper examines the integration of cloud computing and big data analytics, detailing its benefits (e.g., scalability, cost savings), challenges (e.g., security, data heterogeneity), and practicalimplementations (e.g., service models, workflows, and tools like AWS Redshift and Google BigQuery). Through a systematic literature review and comparative analysis of 32 studies, we highlight real-world applications and gaps for future research. The results affirm the synergy’s potential while stressing the need for improved security and standardization.