Big Data Analytics

Designed for the students of B.E./B.Tech (Computer Science and Engineering/IT), M.Sc (Computer Science), MCA, and M.Sc (Data Science), this textbook mainly focuses on issues and solutions concerned with data explosion problems. Without the prior knowledge of database world, the reader of this book can easily understand the evolution of database technology in handling big data.

With a focus on the analytical theory to handle high dimensional data, this text also presents illustrations using analytical tool R. The role of real-time system architecture and platforms, Hadoop ecosystem components and NoSQL database MongoDB to handle big data is also elaborated. Each chapter ends with exercise problems and multiple-choice questions, which will motivate the readers to further analyse the applicability of concepts.

Distinctive Features - Worked out coding using R and MongoDB and related questions using these platforms
- Various analytical techniques with sample data (such as clustering, classification, rough set theory, association rules)
- Basics of real-time processing, issues and remedies
- Several types of data, including time-series data, correlations among data and remedial techniques to handle the issues raised in the underlying domain
- Case studies/examples for in-depth understanding among the students

TARGET AUDIENCE - B.E./B.Tech (Computer Science and Engineering/IT)
- M.Sc (Computer Science/Data Science)
- MCA