Rawat S. Data Analytics using Machine Learning Techniques...Cloud Platforms 2026

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Rawat S. Data Analytics using Machine Learning Techniques...Cloud Platforms 2026

Textbook in PDF format Data Analytics using Machine Learning Techniques on Cloud Platforms examines how Machine Learning (ML) and Cloud Computing combine to drive data-driven decision-making across industries. Covering ML techniques, loud-based analytics tools and security concerns, this book provides theoretical foundations and real-world applications in fields like healthcare, logistics and e-commerce. It also addresses security challenges, privacy concerns and compliance frameworks, ensuring a comprehensive understanding of cloud-based analytics. The journey begins with insights into what data analytics are like, where it started, how it looks like in a Big Data era. The book then turns to relevant challenges that industries are currently facing in the data management sphere, analysing necessary tools and technologies such as Apache Hadoop, Tableau and Power BI, which are crucial for analytical processes. The emphasis on statistical methods and ML toolchains equips the audience with the necessary skill set to comprehend predictive analytics models and the deployment of such models. The book discusses the potential of ML by introducing methods like neural networks, supervised and unsupervised learning, regression, clustering and others and demonstrating how they are used in many fields. Along with describing cloud computing’s architecture, advantages and integration with analytics to promote scalability and agility, it also examines the revolutionary role of cloud computing. Examples from e-commerce, logistics, healthcare and education highlight the transformative potential of combining data analytics, ML and cloud computing, and driving innovation and efficiency across industries. These technologies empower businesses to make data-driven decisions, optimize operations and improve user experiences. The book also focuses on important aspects such as security and privacy concerns which are very important in the cloud age. Also, it provides a good exploration of new advancements that are expected to give a beacon of hope on the advancements of AI analytics in businesses and the society as a whole. Preface Introduction Data Analytics and Compliance in Cloud-Machine Learning Data Analytics: Tools and Technologies Data Analytics: Statistical Approach Supervised and Unsupervised Methods of Machine Learning Used in Data Analytics Opportunities and Challenges for Data Analytics Integrated with Machine Learning Cloud Computing: A Change in the IT Infrastructure Landscape Redefining Data Analytics with ML and Cloud Data Analytics and Cloud Together: A Powerful Combination for E-Commerce and Supply Chain Logistics Data Analytics, Machine Learning and Cloud Together: A Powerful Combination for Healthcare and Education Security and Privacy Issues for Data Analytics Using Machine Learning in Cloud Computing Future Trends for ML-Based Data Analytics in the Cloud