Big data management and analytics : Concepts, tools, and applications/ By Rajesh Jugulum, David J. Fogarty, Chris Heien, Surya Putchala.

By:

Jugulum, Rajesh

Contributor(s):

Material type: Text

TextLanguage: English Publisher: Boca Raton, FL : CRC Press, 2025Edition: First editionDescription: 186 Pages: illustrations; 24 cmContent type:

rdacontent

Media type:

unmediated

Carrier type:

volume

ISBN:

9781032040400

Subject(s):

LOC classification:

QA76.9.D343 .J84 2025.

Contents:

Foreword Preface and Acknowledgements Authors Chapter 1 - The Management of BIG Data Overview Chapter 2 - Big Data, Hadoop Distro, Data Triad, and Enterprise Data Lakes Chapter 3 - The Data Supply Chain Chapter 4 - Data Quality – Measurement and Its Impact Chapter 5 - Analytics Landscape, Execution, and Evaluation Chapter 6 - Big Data and Cloud Solutions Chapter 7 - Structuring Unstructured Data and NoSQL Chapter 8 - Design and Development of Multivariate Diagnostic Systems Chapter 9 - Big Data and Artificial Intelligence (AI) Chapter 10 - Aligning Big Data and AI Strategy with Business Goals Chapter 11 - Facets of Responsible AI References Appendixes

Summary: Description As more companies go digital and conduct their business online, this book provides practical examples of how they can better manage their data and use it to generate maximum value. It offers an integrated approach by treating data as an asset and discusses how to preserve and protect it just like any other corporate asset. Big Data Management and Analytics: Concepts, Tools, and Applications illustrates effective strategies for managing, governing, and analyzing big data to gain a competitive edge for companies utilizing big data and analytics. It offers a comprehensive guide on methods, tools, and concepts to efficiently manage and analyze big data in order to make informed decisions. Additionally, this book explores the significance of artificial intelligence and machine learning in leveraging big data and how they can be optimized in a well-structured environment. This book also emphasizes treating big data as a valuable asset and outlines strategies for preserving and safeguarding it like any other corporate asset. The inclusion of case studies ensures that the methodologies and concepts presented can be easily implemented in day-to-day operations. Given the current significance of big data in the business world, this book equips readers with the necessary skills to effectively manage this valuable asset. It is tailored for practitioners, students, and professionals working in data mining, big data, and machine learning across various industries, including manufacturing.

List(s) this item appears in: Technical Electives - Bachelor of Science in Oil and Gas Engineering (CET)

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode
Books	MAIN	College of Engineering and Technology (CET)	QA76.9.D343 .J84 2025 (Browse shelf(Opens below))	Available		00000238

Includes bibliographical references and index.

Foreword

Preface and Acknowledgements

Authors

Chapter 1 - The Management of BIG Data Overview

Chapter 2 - Big Data, Hadoop Distro, Data Triad, and Enterprise Data Lakes

Chapter 3 - The Data Supply Chain

Chapter 4 - Data Quality – Measurement and Its Impact

Chapter 5 - Analytics Landscape, Execution, and Evaluation

Chapter 6 - Big Data and Cloud Solutions

Chapter 7 - Structuring Unstructured Data and NoSQL

Chapter 8 - Design and Development of Multivariate Diagnostic Systems

Chapter 9 - Big Data and Artificial Intelligence (AI)

Chapter 10 - Aligning Big Data and AI Strategy with Business Goals

Chapter 11 - Facets of Responsible AI

References

Appendixes

Description
As more companies go digital and conduct their business online, this book provides practical examples of how they can better manage their data and use it to generate maximum value. It offers an integrated approach by treating data as an asset and discusses how to preserve and protect it just like any other corporate asset.

Big Data Management and Analytics: Concepts, Tools, and Applications illustrates effective strategies for managing, governing, and analyzing big data to gain a competitive edge for companies utilizing big data and analytics. It offers a comprehensive guide on methods, tools, and concepts to efficiently manage and analyze big data in order to make informed decisions. Additionally, this book explores the significance of artificial intelligence and machine learning in leveraging big data and how they can be optimized in a well-structured environment. This book also emphasizes treating big data as a valuable asset and outlines strategies for preserving and safeguarding it like any other corporate asset. The inclusion of case studies ensures that the methodologies and concepts presented can be easily implemented in day-to-day operations.

Given the current significance of big data in the business world, this book equips readers with the necessary skills to effectively manage this valuable asset. It is tailored for practitioners, students, and professionals working in data mining, big data, and machine learning across various industries, including manufacturing.

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