Big Data: A Tutorial-Based Approach
Autor Nasir Raheemen Limba Engleză Hardback – 25 feb 2019
Features
- Identifies the primary drivers of Big Data
- Walks readers through the theory, methods and technology of Big Data
- Explains how to handle the 4 V’s of Big Data in order to extract value for better business decision making
- Shows how and why data connectors are critical and necessary for Agile text analytics
- Includes in-depth tutorials to perform necessary set-ups, installation, configuration and execution of important tasks
- Explains the command line as well as GUI interface to a powerful data exchange tool between Hadoop and legacy r-dbms databases
| Toate formatele și edițiile | Preț | Express |
|---|---|---|
| Paperback (1) | 147.82 lei 6-8 săpt. | |
| CRC Press – 30 sep 2020 | 147.82 lei 6-8 săpt. | |
| Hardback (1) | 338.08 lei 6-8 săpt. | |
| CRC Press – 25 feb 2019 | 338.08 lei 6-8 săpt. |
Preț: 338.08 lei
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Specificații
ISBN-13: 9780367183455
ISBN-10: 0367183455
Pagini: 202
Ilustrații: 3 Tables, black and white; 43 Illustrations, black and white
Dimensiuni: 138 x 216 x 17 mm
Greutate: 1.2 kg
Ediția:1
Editura: CRC Press
Colecția Chapman and Hall/CRC
ISBN-10: 0367183455
Pagini: 202
Ilustrații: 3 Tables, black and white; 43 Illustrations, black and white
Dimensiuni: 138 x 216 x 17 mm
Greutate: 1.2 kg
Ediția:1
Editura: CRC Press
Colecția Chapman and Hall/CRC
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Cuprins
Chapter 1: Introduction to Big Data
Chapter 2: Big Data Implementation
Chapter 3: Big Data Use Cases
Chapter 4: Big Data Migration
Chapter 5: Big Data Ingestion, Integration, and Management
Chapter 6: Big Data Repository
Chapter 7: Big Data Visualization
Chapter 8: Structured and Un-Structured Data Analytics
Chapter 9: Data Virtualization
Chapter 10: Cloud Computing
Chapter 2: Big Data Implementation
Chapter 3: Big Data Use Cases
Chapter 4: Big Data Migration
Chapter 5: Big Data Ingestion, Integration, and Management
Chapter 6: Big Data Repository
Chapter 7: Big Data Visualization
Chapter 8: Structured and Un-Structured Data Analytics
Chapter 9: Data Virtualization
Chapter 10: Cloud Computing
Recenzii
[Big Data: A Tutorial-Based Approach] is a well thought-out guide, comprising of tutorials and graphic illustrations, that builds an integrated approach which clearly answers the ‘What’ and the ‘How’ and the ‘Why’ of ‘Big Data’. It takes the readers on an inquisitive journey through the information wonderland of data lakes and provides the tools and techniques to bring about the marriage of structured and unstructured data.
It is a must-read primer that keeps its eyes always set on the end goal of extracting useful business insight from ‘Big Data’ by fully exploiting the potential of Hadoop Distributed File System Infrastructure, MapReduce processing, and Agile Data Analytics to implement proper Data Migration, Data Ingestion, Data Management, Data Analytics, Data Visualization and Data Virtualization processes.
Last but not the least, this book finally tests the readers on their understanding of ‘Big Data’ in the form of a QUIZ.
-Dr. Sohail Subhani, Winona State University
This is a strong text that provides substantial direction and detail about elemental data science concepts. A key strength of this book is its focus on data processing and handling techniques, an area of data science that is often overlooked. Raheem brings significant experience and subject matter expertise to this practical text. The book's tutorial approach allows the reader to gain practical experience in the areas discussed. Systems and programs covered include Hadoop, MapReduce, Hive, Yarn, Sqoop, and Tableau. The text also includes use cases that apply concepts presented in realworld scenarios. The text's regular self-assessment quizzes, with answers provided, allow users to evaluate their progress. Big Data is recommended for higher-level computer science students studying big data. The structure and breadth of topics covered make it a useful textbook for a 500-level computer science course in big data, though it would also be valuable as a reference or for self-study.
--K. J. Whitehair, independent scholar
Summing Up: Recommended. Advanced undergraduates through faculty and professionals.
[Big Data: A Tutorial-Based Approach] is a well thought-out guide, comprising of tutorials and graphic illustrations, that builds an integrated approach which clearly answers the ‘What’ and the ‘How’ and the ‘Why’ of ‘Big Data’. It takes the readers on an inquisitive journey through the information wonderland of data lakes and provides the tools and techniques to bring about the marriage of structured and unstructured data.
It is a must-read primer that keeps its eyes always set on the end goal of extracting useful business insight from ‘Big Data’ by fully exploiting the potential of Hadoop Distributed File System Infrastructure, MapReduce processing, and Agile Data Analytics to implement proper Data Migration, Data Ingestion, Data Management, Data Analytics, Data Visualization and Data Virtualization processes.
Last but not the least, this book finally tests the readers on their understanding of ‘Big Data’ in the form of a QUIZ.
-Dr. Sohail Subhani, Winona State University
It is a must-read primer that keeps its eyes always set on the end goal of extracting useful business insight from ‘Big Data’ by fully exploiting the potential of Hadoop Distributed File System Infrastructure, MapReduce processing, and Agile Data Analytics to implement proper Data Migration, Data Ingestion, Data Management, Data Analytics, Data Visualization and Data Virtualization processes.
Last but not the least, this book finally tests the readers on their understanding of ‘Big Data’ in the form of a QUIZ.
-Dr. Sohail Subhani, Winona State University
This is a strong text that provides substantial direction and detail about elemental data science concepts. A key strength of this book is its focus on data processing and handling techniques, an area of data science that is often overlooked. Raheem brings significant experience and subject matter expertise to this practical text. The book's tutorial approach allows the reader to gain practical experience in the areas discussed. Systems and programs covered include Hadoop, MapReduce, Hive, Yarn, Sqoop, and Tableau. The text also includes use cases that apply concepts presented in realworld scenarios. The text's regular self-assessment quizzes, with answers provided, allow users to evaluate their progress. Big Data is recommended for higher-level computer science students studying big data. The structure and breadth of topics covered make it a useful textbook for a 500-level computer science course in big data, though it would also be valuable as a reference or for self-study.
--K. J. Whitehair, independent scholar
Summing Up: Recommended. Advanced undergraduates through faculty and professionals.
[Big Data: A Tutorial-Based Approach] is a well thought-out guide, comprising of tutorials and graphic illustrations, that builds an integrated approach which clearly answers the ‘What’ and the ‘How’ and the ‘Why’ of ‘Big Data’. It takes the readers on an inquisitive journey through the information wonderland of data lakes and provides the tools and techniques to bring about the marriage of structured and unstructured data.
It is a must-read primer that keeps its eyes always set on the end goal of extracting useful business insight from ‘Big Data’ by fully exploiting the potential of Hadoop Distributed File System Infrastructure, MapReduce processing, and Agile Data Analytics to implement proper Data Migration, Data Ingestion, Data Management, Data Analytics, Data Visualization and Data Virtualization processes.
Last but not the least, this book finally tests the readers on their understanding of ‘Big Data’ in the form of a QUIZ.
-Dr. Sohail Subhani, Winona State University
Descriere
This book explores the tools and techniques to bring about the marriage of structured and unstructured data.
Notă biografică
Nasir Raheem is an accomplished, innovative, and results-driven project manager, architect and business analyst with over 20 years of wide-ranging experience encompassing I.T Infra-structure design, planning and implementation of highly integrated systems that included Big Data (HIVE) Database Administration, Business Re-engineering, Asset & Data management (ServiceNow), Data Integration, Data Modeling, Disaster Recovery and ERP Database /Application cloning projects. He is an experienced manager of IT projects related to multi-billion dollar corporate mergers, migration, server upgrades, database upgrades, data conversion, cloning and integration of supply chain management ERP and CRM application modules at Wells Fargo Bank, WebTV (now Microsoft) and Hitachi Global Storage Technologies (now Western Digital). He is also a published author and instructor of an online course approved by Harvard University Innovation Lab, ‘March towards Big Data.’