Comprehensive Strategies for Cloud-Driven Data Analytics Pipelines Incorporating Machine Learning Algorithms and Optimized Database Architectures in Modern Information Technology Systems
Keywords:
Cloud computing, data analytics, machine learning, database architecture, IT systems, scalability, pipeline optimizationAbstract
Cloud-driven data analytics pipelines have revolutionized modern IT systems, offering robust mechanisms for processing vast volumes of data. Integrating machine learning (ML) algorithms and optimized database architectures enhances efficiency, scalability, and decision-making capabilities. This paper explores key strategies for designing and implementing such pipelines. A detailed analysis of existing literature highlights the benefits and challenges of adopting cloud platforms for analytics. Emphasis is placed on ML integration and the role of database architectures tailored for high-performance environments. Practical recommendations and case studies are included to offer actionable insights.
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Copyright (c) 2024 Syed Tahaseen (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
