Big data simplified / (Record no. 23820)

MARC details
000 -LEADER
fixed length control field 01944nam a22002057a 4500
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9789353435110
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title English
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 005.7
Item number MUK
100 ## - MAIN ENTRY--AUTHOR NAME
Author name Mukherjee, Sourabh
245 ## - TITLE STATEMENT
Title Big data simplified /
Statement of responsibility, etc Sourabh Mukherjee, Amit Kumar Das and Sayan Goswami
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication New Delhi :
Name of publisher Pearson ,
Year of publication 2019 .
300 ## - PHYSICAL DESCRIPTION
Number of Pages xxx, 329 Pg.;
Other physical details ill :
Dimensions 25 cm.
500 ## - GENERAL NOTE
General note 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, Apache Zookeeper, Flume, Kafka, Spark, Python and NoSQL databases like Cassandra, MongoDB, graphs, 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. 3. Numerous objective and subjective-type questions added for readers to evaluate their learning
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc include index
505 ## - FORMATTED CONTENTS NOTE
Formatted contents note 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 Big Data 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
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Subject big data
700 ## - ADDED ENTRY--PERSONAL NAME
Author 2/ Editor Amit Kumar, Das
700 ## - ADDED ENTRY--PERSONAL NAME
Author 2/ Editor Goswami, Sayan
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Shelving location Date acquired Source of acquisition Cost, normal purchase price Bill Date Full call number Accession Number Price effective from Koha item type
    Dewey Decimal Classification     Institute of Public Enterprise, Library Institute of Public Enterprise, Library S Campus 05/16/2025 Synergy Books India 780.00 18-04-2025 005.7 MUK 50050 05/16/2025 Books
    Dewey Decimal Classification     Institute of Public Enterprise, Library Institute of Public Enterprise, Library S Campus 05/16/2025 Synergy Books India 780.00 18-04-2025 005.7 MUK 50051 05/16/2025 Books
    Dewey Decimal Classification     Institute of Public Enterprise, Library Institute of Public Enterprise, Library S Campus 05/16/2025 Synergy Books India 780.00 18-04-2025 005.7 MUK 50052 05/16/2025 Books
    Dewey Decimal Classification     Institute of Public Enterprise, Library Institute of Public Enterprise, Library S Campus 05/16/2025 Synergy Books India 780.00 18-04-2025 005.7 MUK 50053 05/16/2025 Books

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