OPTIMIZING CLOUD DATA MANAGEMENT WITH AI-DRIVEN SOLUTIONS
OPTIMIZING CLOUD DATA MANAGEMENT WITH AI-DRIVEN SOLUTIONS

Author(s): Iviana Hristova
Subject(s): Economy, Business Economy / Management, ICT Information and Communications Technologies
Published by: Икономически университет - Варна
Keywords: Artificial Intelligencе; Data Management; Cloud Computing; Google Cloud; BigQuery
Summary/Abstract: In the era of digital transformation, data has become a critical asset for organizations, driving key decision-making and strategic initiatives. As enterprises increasingly shift to cloud infrastructures, managing broad amounts of data has become a central challenge. This paper explores the transformative role of Artificial Intelligence (AI) in enhancing cloud data management processes, focusing on data integrity, predictive analytics for capacity planning, and real-time data integration. AI-driven methodologies, including machine learning and natural language processing, are discussed for their application in automating data quality management, improving resource allocation, and seamlessly integrating disparate data sources.A significant aspect of this exploration includes Google Cloud’s BigQuery, a powerful tool that integrates machine learning capabilities directly within cloud data workflows. BigQuery’s ML integration allows organizations to automate data cleansing processes by detecting and correcting anomalies in real-time, thus ensuring high data accuracy and consistency across datasets. With its built-in SQL support and advanced ML functions, BigQuery enables extensive data analysis without the need for complex infrastructure, making it highly accessible for data engineers and analysts alike.The study further highlights BigQuery’s predictive analytics capabilities for capacity planning, enabling organizations to forecast data needs using techniques like time-series analysis. This predictive functionality helps businesses dynamically adjust resources to meet demand, optimizing both performance and cost. Furthermore, BigQuery supports real-time data integration, essential for high-demand applications such as financial analysis and customer engagement, where timely insights are critical. By investigating both the opportunities and limitations, this paper provides a comprehensive understanding of AI's potential in reshaping cloud data management and its future developments.

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