Essentials of Big Data Analytics
Applications in R and Python
Published on 6. January 2026
250 pages
978-0-443-45207-9 (ISBN)
Description
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.
- Includes hands-on Tutorials and Case Studies: Structured exercises and real-world examples reinforce learning and skill-building
- Focuses on Python and R for Big Data: Detailed lessons in Python and R programming cater to the increasing demand for data science expertise
- Balanced Theory and Practice: Comprehensive coverage ensures a strong theoretical foundation paired with actionable insights for real-world application
More details
Other editions
Additional editions
Pallavi Chavan | Kalyani Pampattiwar | Ramchandra Mangrulkar
Essentials of Big Data Analytics
Applications in R and Python
Book
01/2026
Morgan Kaufmann
€175.78
Shipment within 15-20 days
Persons
Dr. Pallavi Vijay Chavan is Professor and head-IT at Ramrao Adik Institute of Technology, D. Y. Patil Deemed to be University, Navi Mumbai, MH, India. She has been in academia for the past 20 years working in the area of computing theory, data science, and network security. In her academic journey, she has published research work in the data science and security domain with reputed publishers including Springer, Elsevier, CRC Press, and Inderscience.Dr. Kalyani Pampattiwar is an Associate 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. 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.Dr. Ramchandra Mangrulkar is a Professor of Information Technology department in Dwarkadas Sanghvi College of Engineering and has 24 years of teaching experience in the field of intelligent systems and security. He completed his M.Tech. in Computer Science and Engineering from NIT Rourkela. He completed his Ph.D. in Information Security at SGBAU, Amravati. He is the recipient of grants from UGC as well as AICTE
Content
1. Introduction to Big Data Analytics2. Mathematical Foundations3. Big Data Technologies and Programming4. Data Ingestion and Preprocessing5. Big Data Storage and Management6. Advanced MapReduce for Big Data Processing7. Machine Learning Techniques for Big Data Processing8. Mining Data Streams9. Case Studies and Practical Applications10. Hands-on Exercises and Tutorials with R, MapReduce, and Data Streams11. Emerging Trends and Future Directions
