Big Data Simplified blends technology with strategy and delves into applications of big data in specialized areas, such as recommendation engines, data science and Internet of Things (IoT) and enables a practitioner to make the right technology choice. The steps to strategize a big data implementation are also discussed in detail. This book presents a holistic approach to the topic, covering a wide landscape of big
data technologies like Hadoop 2.0 and package implementations, such as Cloudera. In-depth discussion of associated technologies, such as MapReduce, Hive, Pig, Oozie, ApacheZookeeper, Flume, Kafka, Spark, Python and NoSQL databases like Cassandra, MongoDB, GraphDB, etc., is also included.
Features:
1. Important concepts are backed by code snippets enabling step-by-step practical implementation
2. Includes case study with complete code and detailing the concepts are discussed
3. Numerous objective and subjective-type questions added for readers to evaluate their learning
Table of Contents:
Chapter 1) A Closer Look at Data
Chapter 2) Introducing Big Data
Chapter 3) Introducing Hadoop
Chapter 4) Introducing MapReduce
Chapter 5) Introducing NoSQL
Chapter 6) Introducing Spark and Kafka
Chapter 7) Other BigData Tools and Technologies
Chapter 8) Working with Big Data in R
Chapter 9) Working with Big Data in Python
Chapter 10) Big Data Applied
Chapter 11) Big Data Strategy
Chapter 12) Case Study: Retail Near Real-time Analytics
About the Author
Sourabh Mukherjee Head –
Data Management Practice
Advanced Technology Center India
Accenture
Amit Kumar Das
Assistant Professor
Department of Computer Science and Engineering
Institute of Engineering and Management, Kolkata
Sayan Goswami
Technical Architect, Big Data
Cognizant Technologies
