AI-DRIVEN DATA ENGINEERING: INNOVATIONS IN CLOUD-BASED INTEGRATION AND PROCESSING

This article dives into the exciting transformation that Artificial Intelligence (AI) brings to data engineering and integration processes within cloud computing environments.It showcases the groundbreaking implementation of AI-driven solutions across various dimensions, such as automated pipeline generation, intelligent schema matching, anomaly detection, and real-time data integration.Using a dynamic mixed-methods approach that combines both quantitative and qualitative analyses, the article reveals astonishing improvements in data processing efficiency, with organizations experiencing up to a 67% reduction in processing time and an incredible 89% boost in accuracy.Featuring compelling case studies from the financial services, healthcare, and e-commerce sectors, the article provides compelling evidence that these innovative systems far surpass traditional methods in cost efficiency, scalability, and data quality management, all while slashing operational overhead.It also tackles the hurdles of implementation, including the integration of legacy systems and the complexities of initial deployment, offering valuable strategic insights for organizations eager to embrace AI in their data engineering workflows.This article contributes to a deeper understanding of how AI technologies can be harnessed to tackle the escalating challenges of data management in cloud computing environments, while laying the groundwork for future advancements in this fast-paced and ever-evolving field.