Big Data Concepts Technologies And Applications

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Big Data Technologies and Applications

Author : Borko Furht
Publisher : Springer
ISBN 13 : 3319445502
Total Pages : 400 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis Big Data Technologies and Applications by : Borko Furht

Download or read book Big Data Technologies and Applications written by Borko Furht and published by Springer. This book was released on 2016-09-16 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: The objective of this book is to introduce the basic concepts of big data computing and then to describe the total solution of big data problems using HPCC, an open-source computing platform. The book comprises 15 chapters broken into three parts. The first part, Big Data Technologies, includes introductions to big data concepts and techniques; big data analytics; and visualization and learning techniques. The second part, LexisNexis Risk Solution to Big Data, focuses on specific technologies and techniques developed at LexisNexis to solve critical problems that use big data analytics. It covers the open source High Performance Computing Cluster (HPCC Systems®) platform and its architecture, as well as parallel data languages ECL and KEL, developed to effectively solve big data problems. The third part, Big Data Applications, describes various data intensive applications solved on HPCC Systems. It includes applications such as cyber security, social network analytics including fraud, Ebola spread modeling using big data analytics, unsupervised learning, and image classification. The book is intended for a wide variety of people including researchers, scientists, programmers, engineers, designers, developers, educators, and students. This book can also be beneficial for business managers, entrepreneurs, and investors.

Big Data Concepts, Technologies, and Applications

Author : Mohammad Shahid Husain
Publisher : Auerbach Publications
ISBN 13 : 9781032579184
Total Pages : 0 pages
Book Rating : 4.5/5 (791 download)

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Book Synopsis Big Data Concepts, Technologies, and Applications by : Mohammad Shahid Husain

Download or read book Big Data Concepts, Technologies, and Applications written by Mohammad Shahid Husain and published by Auerbach Publications. This book was released on 2023-10 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses the issues and challenges faced by researchers as well as the opportunities for practitioners embracing the Big Data paradigm. It explores concepts behind Big Data, data analysis, and potential benefits. Finally, the book explains deriving value from Big Data and covers storage, processing power, and platforms.

Distributed Computing in Big Data Analytics

Author : Sourav Mazumder
Publisher : Springer
ISBN 13 : 3319598341
Total Pages : 162 pages
Book Rating : 4.3/5 (195 download)

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Book Synopsis Distributed Computing in Big Data Analytics by : Sourav Mazumder

Download or read book Distributed Computing in Big Data Analytics written by Sourav Mazumder and published by Springer. This book was released on 2017-08-29 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data technologies are used to achieve any type of analytics in a fast and predictable way, thus enabling better human and machine level decision making. Principles of distributed computing are the keys to big data technologies and analytics. The mechanisms related to data storage, data access, data transfer, visualization and predictive modeling using distributed processing in multiple low cost machines are the key considerations that make big data analytics possible within stipulated cost and time practical for consumption by human and machines. However, the current literature available in big data analytics needs a holistic perspective to highlight the relation between big data analytics and distributed processing for ease of understanding and practitioner use. This book fills the literature gap by addressing key aspects of distributed processing in big data analytics. The chapters tackle the essential concepts and patterns of distributed computing widely used in big data analytics. This book discusses also covers the main technologies which support distributed processing. Finally, this book provides insight into applications of big data analytics, highlighting how principles of distributed computing are used in those situations. Practitioners and researchers alike will find this book a valuable tool for their work, helping them to select the appropriate technologies, while understanding the inherent strengths and drawbacks of those technologies.

Big Data: Concepts, Methodologies, Tools, and Applications

Author : Management Association, Information Resources
Publisher : IGI Global
ISBN 13 : 1466698411
Total Pages : 2478 pages
Book Rating : 4.4/5 (666 download)

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Book Synopsis Big Data: Concepts, Methodologies, Tools, and Applications by : Management Association, Information Resources

Download or read book Big Data: Concepts, Methodologies, Tools, and Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2016-04-20 with total page 2478 pages. Available in PDF, EPUB and Kindle. Book excerpt: The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. Big Data: Concepts, Methodologies, Tools, and Applications is a multi-volume compendium of research-based perspectives and solutions within the realm of large-scale and complex data sets. Taking a multidisciplinary approach, this publication presents exhaustive coverage of crucial topics in the field of big data including diverse applications, storage solutions, analysis techniques, and methods for searching and transferring large data sets, in addition to security issues. Emphasizing essential research in the field of data science, this publication is an ideal reference source for data analysts, IT professionals, researchers, and academics.

Big Data

Author : Balamurugan Balusamy
Publisher : John Wiley & Sons
ISBN 13 : 1119701872
Total Pages : 368 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Big Data by : Balamurugan Balusamy

Download or read book Big Data written by Balamurugan Balusamy and published by John Wiley & Sons. This book was released on 2021-03-15 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn Big Data from the ground up with this complete and up-to-date resource from leaders in the field Big Data: Concepts, Technology, and Architecture delivers a comprehensive treatment of Big Data tools, terminology, and technology perfectly suited to a wide range of business professionals, academic researchers, and students. Beginning with a fulsome overview of what we mean when we say, “Big Data,” the book moves on to discuss every stage of the lifecycle of Big Data. You’ll learn about the creation of structured, unstructured, and semi-structured data, data storage solutions, traditional database solutions like SQL, data processing, data analytics, machine learning, and data mining. You’ll also discover how specific technologies like Apache Hadoop, SQOOP, and Flume work. Big Data also covers the central topic of big data visualization with Tableau, and you’ll learn how to create scatter plots, histograms, bar, line, and pie charts with that software. Accessibly organized, Big Data includes illuminating case studies throughout the material, showing you how the included concepts have been applied in real-world settings. Some of those concepts include: The common challenges facing big data technology and technologists, like data heterogeneity and incompleteness, data volume and velocity, storage limitations, and privacy concerns Relational and non-relational databases, like RDBMS, NoSQL, and NewSQL databases Virtualizing Big Data through encapsulation, partitioning, and isolating, as well as big data server virtualization Apache software, including Hadoop, Cassandra, Avro, Pig, Mahout, Oozie, and Hive The Big Data analytics lifecycle, including business case evaluation, data preparation, extraction, transformation, analysis, and visualization Perfect for data scientists, data engineers, and database managers, Big Data also belongs on the bookshelves of business intelligence analysts who are required to make decisions based on large volumes of information. Executives and managers who lead teams responsible for keeping or understanding large datasets will also benefit from this book.

Big Data

Author : Balamurugan Balusamy
Publisher : John Wiley & Sons
ISBN 13 : 1119701821
Total Pages : 370 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Big Data by : Balamurugan Balusamy

Download or read book Big Data written by Balamurugan Balusamy and published by John Wiley & Sons. This book was released on 2021-04-13 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn Big Data from the ground up with this complete and up-to-date resource from leaders in the field Big Data: Concepts, Technology, and Architecture delivers a comprehensive treatment of Big Data tools, terminology, and technology perfectly suited to a wide range of business professionals, academic researchers, and students. Beginning with a fulsome overview of what we mean when we say, “Big Data,” the book moves on to discuss every stage of the lifecycle of Big Data. You’ll learn about the creation of structured, unstructured, and semi-structured data, data storage solutions, traditional database solutions like SQL, data processing, data analytics, machine learning, and data mining. You’ll also discover how specific technologies like Apache Hadoop, SQOOP, and Flume work. Big Data also covers the central topic of big data visualization with Tableau, and you’ll learn how to create scatter plots, histograms, bar, line, and pie charts with that software. Accessibly organized, Big Data includes illuminating case studies throughout the material, showing you how the included concepts have been applied in real-world settings. Some of those concepts include: The common challenges facing big data technology and technologists, like data heterogeneity and incompleteness, data volume and velocity, storage limitations, and privacy concerns Relational and non-relational databases, like RDBMS, NoSQL, and NewSQL databases Virtualizing Big Data through encapsulation, partitioning, and isolating, as well as big data server virtualization Apache software, including Hadoop, Cassandra, Avro, Pig, Mahout, Oozie, and Hive The Big Data analytics lifecycle, including business case evaluation, data preparation, extraction, transformation, analysis, and visualization Perfect for data scientists, data engineers, and database managers, Big Data also belongs on the bookshelves of business intelligence analysts who are required to make decisions based on large volumes of information. Executives and managers who lead teams responsible for keeping or understanding large datasets will also benefit from this book.

Machine Learning and Big Data

Author : Uma N. Dulhare
Publisher : John Wiley & Sons
ISBN 13 : 1119654742
Total Pages : 544 pages
Book Rating : 4.1/5 (196 download)

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Book Synopsis Machine Learning and Big Data by : Uma N. Dulhare

Download or read book Machine Learning and Big Data written by Uma N. Dulhare and published by John Wiley & Sons. This book was released on 2020-09-01 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended for academic and industrial developers, exploring and developing applications in the area of big data and machine learning, including those that are solving technology requirements, evaluation of methodology advances and algorithm demonstrations. The intent of this book is to provide awareness of algorithms used for machine learning and big data in the academic and professional community. The 17 chapters are divided into 5 sections: Theoretical Fundamentals; Big Data and Pattern Recognition; Machine Learning: Algorithms & Applications; Machine Learning's Next Frontier and Hands-On and Case Study. While it dwells on the foundations of machine learning and big data as a part of analytics, it also focuses on contemporary topics for research and development. In this regard, the book covers machine learning algorithms and their modern applications in developing automated systems. Subjects covered in detail include: Mathematical foundations of machine learning with various examples. An empirical study of supervised learning algorithms like Naïve Bayes, KNN and semi-supervised learning algorithms viz. S3VM, Graph-Based, Multiview. Precise study on unsupervised learning algorithms like GMM, K-mean clustering, Dritchlet process mixture model, X-means and Reinforcement learning algorithm with Q learning, R learning, TD learning, SARSA Learning, and so forth. Hands-on machine leaning open source tools viz. Apache Mahout, H2O. Case studies for readers to analyze the prescribed cases and present their solutions or interpretations with intrusion detection in MANETS using machine learning. Showcase on novel user-cases: Implications of Electronic Governance as well as Pragmatic Study of BD/ML technologies for agriculture, healthcare, social media, industry, banking, insurance and so on.

Big Data Concepts, Theories, and Applications

Author : Shui Yu
Publisher : Springer
ISBN 13 : 3319277634
Total Pages : 437 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Big Data Concepts, Theories, and Applications by : Shui Yu

Download or read book Big Data Concepts, Theories, and Applications written by Shui Yu and published by Springer. This book was released on 2016-03-03 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers three major parts of Big Data: concepts, theories and applications. Written by world-renowned leaders in Big Data, this book explores the problems, possible solutions and directions for Big Data in research and practice. It also focuses on high level concepts such as definitions of Big Data from different angles; surveys in research and applications; and existing tools, mechanisms, and systems in practice. Each chapter is independent from the other chapters, allowing users to read any chapter directly. After examining the practical side of Big Data, this book presents theoretical perspectives. The theoretical research ranges from Big Data representation, modeling and topology to distribution and dimension reducing. Chapters also investigate the many disciplines that involve Big Data, such as statistics, data mining, machine learning, networking, algorithms, security and differential geometry. The last section of this book introduces Big Data applications from different communities, such as business, engineering and science. Big Data Concepts, Theories and Applications is designed as a reference for researchers and advanced level students in computer science, electrical engineering and mathematics. Practitioners who focus on information systems, big data, data mining, business analysis and other related fields will also find this material valuable.

Big Data Management, Technologies, and Applications

Author : Hu, Wen-Chen
Publisher : IGI Global
ISBN 13 : 1466647000
Total Pages : 342 pages
Book Rating : 4.4/5 (666 download)

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Book Synopsis Big Data Management, Technologies, and Applications by : Hu, Wen-Chen

Download or read book Big Data Management, Technologies, and Applications written by Hu, Wen-Chen and published by IGI Global. This book was released on 2013-10-31 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book discusses the exponential growth of information size and the innovative methods for data capture, storage, sharing, and analysis for big data"--Provided by publisher.

Big Data Applications and Use Cases

Author : Patrick C. K. Hung
Publisher : Springer
ISBN 13 : 3319301462
Total Pages : 214 pages
Book Rating : 4.3/5 (193 download)

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Book Synopsis Big Data Applications and Use Cases by : Patrick C. K. Hung

Download or read book Big Data Applications and Use Cases written by Patrick C. K. Hung and published by Springer. This book was released on 2016-05-18 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents different use cases in big data applications and related practical experiences. Many businesses today are increasingly interested in utilizing big data technologies for supporting their business intelligence so that it is becoming more and more important to understand the various practical issues from different practical use cases. This book provides clear proof that big data technologies are playing an ever increasing important and critical role in a new cross-discipline research between computer science and business.

Big Data

Author : Balamurugan Balusamy
Publisher :
ISBN 13 : 9781119701859
Total Pages : pages
Book Rating : 4.7/5 (18 download)

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Book Synopsis Big Data by : Balamurugan Balusamy

Download or read book Big Data written by Balamurugan Balusamy and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book offers comprehensive coverage of Big Data tools, terminologies and technologies for researchers, business professionals and graduates. This book begins with an overview of what Big Data is and emphasizes all the key concepts of big data end to end. Big Data concepts, technologies, terminologies and storing, processing and analysis techniques and much more -- are all logically organized and reinforced by diagrams and case studies. This book refines readers' understanding of Big Data with in-depth analysis of key concepts. The case studies provided in this book give insight on key concepts. The initial chapters of the book shed light on various characteristics of Big Data that distinguish it from traditional Database Management systems. Big Data Analytics are covered in detail in a separate chapter. Hadoop, the heart of Big Data is handled in the Big Data processing chapter and a deep understanding of its concepts is provided"--

Big Data Applications in Industry 4.0

Author : P. Kaliraj
Publisher : CRC Press
ISBN 13 : 1000537668
Total Pages : 446 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Big Data Applications in Industry 4.0 by : P. Kaliraj

Download or read book Big Data Applications in Industry 4.0 written by P. Kaliraj and published by CRC Press. This book was released on 2022-02-10 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: Industry 4.0 is the latest technological innovation in manufacturing with the goal to increase productivity in a flexible and efficient manner. Changing the way in which manufacturers operate, this revolutionary transformation is powered by various technology advances including Big Data analytics, Internet of Things (IoT), Artificial Intelligence (AI), and cloud computing. Big Data analytics has been identified as one of the significant components of Industry 4.0, as it provides valuable insights for smart factory management. Big Data and Industry 4.0 have the potential to reduce resource consumption and optimize processes, thereby playing a key role in achieving sustainable development. Big Data Applications in Industry 4.0 covers the recent advancements that have emerged in the field of Big Data and its applications. The book introduces the concepts and advanced tools and technologies for representing and processing Big Data. It also covers applications of Big Data in such domains as financial services, education, healthcare, biomedical research, logistics, and warehouse management. Researchers, students, scientists, engineers, and statisticians can turn to this book to learn about concepts, technologies, and applications that solve real-world problems. Features An introduction to data science and the types of data analytics methods accessible today An overview of data integration concepts, methodologies, and solutions A general framework of forecasting principles and applications, as well as basic forecasting models including naïve, moving average, and exponential smoothing models A detailed roadmap of the Big Data evolution and its related technological transformation in computing, along with a brief description of related terminologies The application of Industry 4.0 and Big Data in the field of education The features, prospects, and significant role of Big Data in the banking industry, as well as various use cases of Big Data in banking, finance services, and insurance Implementing a Data Lake (DL) in the cloud and the significance of a data lake in decision making

Big Data Concepts, Technologies, and Applications

Author : Mohammad Shahid Husain
Publisher : CRC Press
ISBN 13 : 1000965074
Total Pages : 124 pages
Book Rating : 4.0/5 (9 download)

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Book Synopsis Big Data Concepts, Technologies, and Applications by : Mohammad Shahid Husain

Download or read book Big Data Concepts, Technologies, and Applications written by Mohammad Shahid Husain and published by CRC Press. This book was released on 2023-10-25 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the advent of such advanced technologies as cloud computing, the Internet of Things, the Medical Internet of Things, the Industry Internet of Things and sensor networks as well as the exponential growth in the usage of Internet-based and social media platforms, there are enormous oceans of data. These huge volumes of data can be used for effective decision making and improved performance if analyzed properly. Due to its inherent characteristics, big data is very complex and cannot be handled and processed by traditional database management approaches. There is a need for sophisticated approaches, tools and technologies that can be used to store, manage and analyze these enormous amounts of data to make the best use of them. Big Data Concepts, Technologies, and Applications covers the concepts, technologies, and applications of big data analytics. Presenting the state-of-the-art technologies in use for big data analytics. it provides an in-depth discussion about the important sectors where big data analytics has proven to be very effective in improving performance and helping industries to remain competitive. This book provides insight into the novel areas of big data analytics and the research directions for the scholars working in the domain. Highlights include: The advantages, disadvantages and challenges of big data analytics State-of-the-art technologies for big data analytics such as Hadoop, NoSQL databases, data lakes, deep learning and blockchain The application of big data analytic in healthcare, business, social media analytics, fraud detection and prevention and governance Exploring the concepts and technologies behind big data analytics, the book is an ideal resource for researchers, students, data scientists, data analysts and business analysts who need insight into big data analytics

Big Data Analysis for Green Computing

Author : Rohit Sharma
Publisher : CRC Press
ISBN 13 : 1000481786
Total Pages : 175 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Big Data Analysis for Green Computing by : Rohit Sharma

Download or read book Big Data Analysis for Green Computing written by Rohit Sharma and published by CRC Press. This book was released on 2021-10-28 with total page 175 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on big data in business intelligence, data management, machine learning, cloud computing, and smart cities. It also provides an interdisciplinary platform to present and discuss recent innovations, trends, and concerns in the fields of big data and analytics. Big Data Analysis for Green Computing: Concepts and Applications presents the latest technologies and covers the major challenges, issues, and advances of big data and data analytics in green computing. It explores basic as well as high-level concepts. It also includes the use of machine learning using big data and discusses advanced system implementation for smart cities. The book is intended for business and management educators, management researchers, doctoral scholars, university professors, policymakers, and higher academic research organizations.

Big Data Computing

Author : Rajendra Akerkar
Publisher : CRC Press
ISBN 13 : 1466578378
Total Pages : 566 pages
Book Rating : 4.4/5 (665 download)

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Book Synopsis Big Data Computing by : Rajendra Akerkar

Download or read book Big Data Computing written by Rajendra Akerkar and published by CRC Press. This book was released on 2013-12-05 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to market forces and technological evolution, Big Data computing is developing at an increasing rate. A wide variety of novel approaches and tools have emerged to tackle the challenges of Big Data, creating both more opportunities and more challenges for students and professionals in the field of data computation and analysis. Presenting a mix of industry cases and theory, Big Data Computing discusses the technical and practical issues related to Big Data in intelligent information management. Emphasizing the adoption and diffusion of Big Data tools and technologies in industry, the book introduces a broad range of Big Data concepts, tools, and techniques. It covers a wide range of research, and provides comparisons between state-of-the-art approaches. Comprised of five sections, the book focuses on: What Big Data is and why it is important Semantic technologies Tools and methods Business and economic perspectives Big Data applications across industries

Big Data

Author : James Warren
Publisher : Simon and Schuster
ISBN 13 : 1638351104
Total Pages : 481 pages
Book Rating : 4.6/5 (383 download)

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Book Synopsis Big Data by : James Warren

Download or read book Big Data written by James Warren and published by Simon and Schuster. This book was released on 2015-04-29 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Big Data teaches you to build big data systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data. It describes a scalable, easy-to-understand approach to big data systems that can be built and run by a small team. Following a realistic example, this book guides readers through the theory of big data systems, how to implement them in practice, and how to deploy and operate them once they're built. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Book Web-scale applications like social networks, real-time analytics, or e-commerce sites deal with a lot of data, whose volume and velocity exceed the limits of traditional database systems. These applications require architectures built around clusters of machines to store and process data of any size, or speed. Fortunately, scale and simplicity are not mutually exclusive. Big Data teaches you to build big data systems using an architecture designed specifically to capture and analyze web-scale data. This book presents the Lambda Architecture, a scalable, easy-to-understand approach that can be built and run by a small team. You'll explore the theory of big data systems and how to implement them in practice. In addition to discovering a general framework for processing big data, you'll learn specific technologies like Hadoop, Storm, and NoSQL databases. This book requires no previous exposure to large-scale data analysis or NoSQL tools. Familiarity with traditional databases is helpful. What's Inside Introduction to big data systems Real-time processing of web-scale data Tools like Hadoop, Cassandra, and Storm Extensions to traditional database skills About the Authors Nathan Marz is the creator of Apache Storm and the originator of the Lambda Architecture for big data systems. James Warren is an analytics architect with a background in machine learning and scientific computing. Table of Contents A new paradigm for Big Data PART 1 BATCH LAYER Data model for Big Data Data model for Big Data: Illustration Data storage on the batch layer Data storage on the batch layer: Illustration Batch layer Batch layer: Illustration An example batch layer: Architecture and algorithms An example batch layer: Implementation PART 2 SERVING LAYER Serving layer Serving layer: Illustration PART 3 SPEED LAYER Realtime views Realtime views: Illustration Queuing and stream processing Queuing and stream processing: Illustration Micro-batch stream processing Micro-batch stream processing: Illustration Lambda Architecture in depth

Big Data Fundamentals

Author : Thomas Erl
Publisher : Prentice Hall
ISBN 13 : 0134291204
Total Pages : 423 pages
Book Rating : 4.1/5 (342 download)

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Book Synopsis Big Data Fundamentals by : Thomas Erl

Download or read book Big Data Fundamentals written by Thomas Erl and published by Prentice Hall. This book was released on 2015-12-29 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: “This text should be required reading for everyone in contemporary business.” --Peter Woodhull, CEO, Modus21 “The one book that clearly describes and links Big Data concepts to business utility.” --Dr. Christopher Starr, PhD “Simply, this is the best Big Data book on the market!” --Sam Rostam, Cascadian IT Group “...one of the most contemporary approaches I’ve seen to Big Data fundamentals...” --Joshua M. Davis, PhD The Definitive Plain-English Guide to Big Data for Business and Technology Professionals Big Data Fundamentals provides a pragmatic, no-nonsense introduction to Big Data. Best-selling IT author Thomas Erl and his team clearly explain key Big Data concepts, theory and terminology, as well as fundamental technologies and techniques. All coverage is supported with case study examples and numerous simple diagrams. The authors begin by explaining how Big Data can propel an organization forward by solving a spectrum of previously intractable business problems. Next, they demystify key analysis techniques and technologies and show how a Big Data solution environment can be built and integrated to offer competitive advantages. Discovering Big Data’s fundamental concepts and what makes it different from previous forms of data analysis and data science Understanding the business motivations and drivers behind Big Data adoption, from operational improvements through innovation Planning strategic, business-driven Big Data initiatives Addressing considerations such as data management, governance, and security Recognizing the 5 “V” characteristics of datasets in Big Data environments: volume, velocity, variety, veracity, and value Clarifying Big Data’s relationships with OLTP, OLAP, ETL, data warehouses, and data marts Working with Big Data in structured, unstructured, semi-structured, and metadata formats Increasing value by integrating Big Data resources with corporate performance monitoring Understanding how Big Data leverages distributed and parallel processing Using NoSQL and other technologies to meet Big Data’s distinct data processing requirements Leveraging statistical approaches of quantitative and qualitative analysis Applying computational analysis methods, including machine learning