Essentials of Big Data Analytics

Applications in R and Python
Erscheinungsjahr 2026
ISBN: 978-0-443-45206-2
Verlag: Elsevier Science

Buch, Englisch, Format (B × H): 191 mm x 235 mm

Essentials of Big Data Analytics: Applications in R and Python is a comprehensive guide that demystifies the complex world of big data analytics, blending theoretical concepts with hands-on practices using the Python and R programming languages and MapReduce framework. This book bridges the gap between theory and practical implementation, providing clear and practical understanding of the key principles and techniques essential for harnessing the power of big data. Essentials of Big Data Analytics is designed to provide a comprehensive resource for readers looking to deepen their understanding of Big Data analytics, particularly within a computer science, engineering, and data science context. By bridging theoretical concepts with practical applications, the book emphasizes hands-on learning through exercises and tutorials, specifically utilizing R and Python. Given the growing role of Big Data in industry and scientific research, this book serves as a timely resource to equip professionals with the skills needed to thrive in data-driven environments.

Autoren/Hrsg.

Chavan, Pallavi

Pampattiwar, Kalyani

Mangrulkar, Ramchandra

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Software Engineering

Inhaltsverzeichnis

1. Introduction to Big Data Analytics
2. Mathematical Foundations
3. Big Data Technologies and Programming
4. Data Ingestion and Preprocessing
5. Big Data Storage and Management
6. Advanced MapReduce for Big Data Processing
7. Machine Learning Techniques for Big Data Processing
8. Mining Data Streams
9. Case Studies and Practical Applications
10. Hands-on Exercises and Tutorials with R, MapReduce, and Data Streams
11. Emerging Trends and Future Directions

Über Autor(innen)

Pampattiwar, Kalyani
Dr. Kalyani Pampattiwar is an Assistant Professor at SIES Graduate School of Technology, Navi Mumbai, MH, India, with 21 years of experience in academia, specializing in blockchain, information security and network security. She earned her doctoral degree in 2023 from D. Y. Patil Deemed to be University, Navi Mumbai, MH, India. She holds the designation of Certified Software Tester and has received research funds from the University of Mumbai. Her research contributions include publications in prestigious international journals, conferences by Inderscience, Springer, and IEEE, as well as book chapters with reputed publishers such as Springer, Elsevier etc. She has received Swayam's "NPTEL Discipline Star" award.

Mangrulkar, Ramchandra
Dr. Mangrulkar is an Assistant Professor of Computer Engineering in the is Dwarkadas Sanghvi College of Engineering and has 20 years of teaching experience in the field of intelligent systems and security. He completed his M.Sc. in Computer Science and Engineering from NIT Rourkela. He completed his Ph.D. in the Information Security from SGBAU, Amravati. Dr. Mangrulkar is the recipient of grants from UGC as well as AICTE.