Big data simplified / (Record no. 23820)
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000 -LEADER | |
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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 |
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 |
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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 |