Big Data: Concepts, Technology, and Architecture

This book provides a comprehensive treatment of Big Data tools, terminology, and technology, suited to a wide range of business professionals, academic researchers, and students. It covers the creation of structured, unstructured, and semi-structured data, data storage solutions, traditional database solutions, data processing, data analytics, machine learning, and data mining. It also covers big data visualization with Tableau and includes case studies to show how the concepts have been applied in real-world settings.

\n Format: Hardback
\n Length: 368 pages
\n Publication date: 15 June 2021
\n Publisher: John Wiley and Sons Ltd
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Big Data: Concepts, Technology, and Architecture is a comprehensive resource that provides a thorough understanding of Big Data tools, terminology, and technology. Designed for a diverse audience of business professionals, academic researchers, and students, this book offers a comprehensive treatment of Big Data's lifecycle, from its definition to its various stages and technologies.

The book begins with an overview of what Big Data encompasses, delving into the creation of structured, unstructured, and semi-structured data. It explores data storage solutions, including traditional database systems like SQL and modern alternatives like NoSQL databases. The book also covers data processing, data analytics, machine learning, and data mining, providing practical insights into these complex topics.

In addition to discussing the technical aspects of Big Data, the book also addresses the central theme of big data visualization with Tableau. It teaches readers how to create various charts and graphs using this powerful software, enabling them to effectively communicate and analyze their data.

Throughout the book, illustrative case studies are included to demonstrate how the concepts discussed have been applied in real-world settings. These case studies cover a wide range of industries and applications, showcasing the practical benefits and challenges of Big Data technology. Some of the key concepts covered include:

Data heterogeneity and incompleteness: Understanding the challenges associated with dealing with diverse and incomplete data sets.

Data volume and velocity: Addressing the issues of handling large amounts of data that are generated and processed at high speeds.

Storage limitations: Exploring strategies for managing and storing massive amounts of data efficiently.

Privacy concerns: Addressing the ethical and legal considerations related to collecting, storing, and processing personal data.

Relational and non-relational databases: Exploring the differences between traditional relational databases and modern NoSQL databases.

Virtualizing Big Data: Discussing techniques for encapsulating, partitioning, and isolating large data sets, as well as server virtualization for Big Data processing.

Apache software: Introducing popular Apache tools such as Hadoop, Cassandra, Avro, Pig, Mahout, Oozie, and Hive, which are commonly used in Big Data projects.

The Big Data analytics lifecycle: Providing a step-by-step guide to evaluating business cases, preparing data, extracting, transforming, analyzing, and visualizing Big Data for informed decision-making.

Whether you are a business professional seeking to leverage Big Data for competitive advantage, an academic researcher interested in exploring the latest trends and technologies, or a student looking to gain a foundational understanding of Big Data, this book is an invaluable resource. It offers a comprehensive and up-to-date treatment of Big Data, providing readers with the knowledge and tools they need to succeed in this rapidly evolving field.

\n Weight: 642g\n
Dimension: 160 x 240 x 26 (mm)\n
ISBN-13: 9781119701828\n \n