Demirbaga U Big Data Analytics Theory, Techniques, Platforms, and Apps 2024
General:
Name: Demirbaga U Big Data Analytics Theory, Techniques, Platforms, and Apps 2024
Format: pdf
Size: 8.42 MB
Book:
Title: Big Data Analytics
Author: Ümit Demirbaga · Gagangeet Singh Aujla · Anish Jindal · O ˘guzhan Kalyon
Language: angielski
Year: 2024
Subjects: Computers, Database Management, Database Administration & Management
Publisher: Springer-Verlag New York, LLC
ISBN: 9783031556395
Total pages: 299
Description:
This book introduces readers to big data analytics. It covers the background to and the concepts of big data, big data analytics, and cloud computing, along with the process of setting up, configuring, and getting familiar with the big data analytics working environments in the first two chapters. The third chapter provides comprehensive information on big data processing systems – from installing these systems to implementing real-world data applications, along with the necessary codes. The next chapter dives into the details of big data storage technologies, including their types, essentiality, durability, and availability, and reveals their differences in their properties. The fifth and sixth chapters guide the reader through understanding, configuring, and performing the monitoring and debugging of big data systems and present the available commercial and open-source tools for this purpose. Chapter seven gives information about a trending machine learning, Bayesian network: a probabilistic graphical model, by presenting a real-world probabilistic application to understand causal, complex, and hidden relationships for diagnosis and forecasting in a scalable manner for big data. Special sections throughout the eighth chapter present different case studies and applications to help the readers to develop their big data analytics skills using various big data analytics frameworks.
The book will be of interest to business executives and IT managers as well as university students and their course leaders, in fact all those who want to get involved in the big data world.
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