Building Big Data Applications

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Building Big Data Applications

Krish Krishnan
Building Big Data Applications Book PDF

Author : Krish Krishnan
Publisher : Academic Press
Page : 242 pages
File Size : 47,9 Mb
Release : 2019-11-15
Category : Computers
ISBN : 9780128158043

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Building Big Data Applications by Krish Krishnan Pdf

Building Big Data Applications helps data managers and their organizations make the most of unstructured data with an existing data warehouse. It provides readers with what they need to know to make sense of how Big Data fits into the world of Data Warehousing. Readers will learn about infrastructure options and integration and come away with a solid understanding on how to leverage various architectures for integration. The book includes a wide range of use cases that will help data managers visualize reference architectures in the context of specific industries (healthcare, big oil, transportation, software, etc.). Explores various ways to leverage Big Data by effectively integrating it into the data warehouse Includes real-world case studies which clearly demonstrate Big Data technologies Provides insights on how to optimize current data warehouse infrastructure and integrate newer infrastructure matching data processing workloads and requirements

Designing Data-Intensive Applications

Martin Kleppmann
Designing Data Intensive Applications Book PDF

Author : Martin Kleppmann
Publisher : "O'Reilly Media, Inc."
Page : 658 pages
File Size : 46,8 Mb
Release : 2017-03-16
Category : Computers
ISBN : 9781491903100

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Designing Data-Intensive Applications by Martin Kleppmann Pdf

Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords? In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures

Big Data Applications in Industry 4.0

P. Kaliraj,T. Devi
Big Data Applications in Industry 4 0 Book PDF

Author : P. Kaliraj,T. Devi
Publisher : CRC Press
Page : 446 pages
File Size : 44,7 Mb
Release : 2022-02-10
Category : Computers
ISBN : 9781000537666

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Big Data Applications in Industry 4.0 by P. Kaliraj,T. Devi Pdf

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

Building Big Data and Analytics Solutions in the Cloud

Wei-Dong Zhu,Manav Gupta,Ven Kumar,Sujatha Perepa,Arvind Sathi,Craig Statchuk,IBM Redbooks
Building Big Data and Analytics Solutions in the Cloud Book PDF

Author : Wei-Dong Zhu,Manav Gupta,Ven Kumar,Sujatha Perepa,Arvind Sathi,Craig Statchuk,IBM Redbooks
Publisher : IBM Redbooks
Page : 101 pages
File Size : 46,9 Mb
Release : 2014-12-08
Category : Computers
ISBN : 9780738453996

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Building Big Data and Analytics Solutions in the Cloud by Wei-Dong Zhu,Manav Gupta,Ven Kumar,Sujatha Perepa,Arvind Sathi,Craig Statchuk,IBM Redbooks Pdf

Big data is currently one of the most critical emerging technologies. Organizations around the world are looking to exploit the explosive growth of data to unlock previously hidden insights in the hope of creating new revenue streams, gaining operational efficiencies, and obtaining greater understanding of customer needs. It is important to think of big data and analytics together. Big data is the term used to describe the recent explosion of different types of data from disparate sources. Analytics is about examining data to derive interesting and relevant trends and patterns, which can be used to inform decisions, optimize processes, and even drive new business models. With today's deluge of data comes the problems of processing that data, obtaining the correct skills to manage and analyze that data, and establishing rules to govern the data's use and distribution. The big data technology stack is ever growing and sometimes confusing, even more so when we add the complexities of setting up big data environments with large up-front investments. Cloud computing seems to be a perfect vehicle for hosting big data workloads. However, working on big data in the cloud brings its own challenge of reconciling two contradictory design principles. Cloud computing is based on the concepts of consolidation and resource pooling, but big data systems (such as Hadoop) are built on the shared nothing principle, where each node is independent and self-sufficient. A solution architecture that can allow these mutually exclusive principles to coexist is required to truly exploit the elasticity and ease-of-use of cloud computing for big data environments. This IBM® RedpaperTM publication is aimed at chief architects, line-of-business executives, and CIOs to provide an understanding of the cloud-related challenges they face and give prescriptive guidance for how to realize the benefits of big data solutions quickly and cost-effectively.

Big Data

Kuan-Ching Li,Hai Jiang,Laurence T. Yang,Alfredo Cuzzocrea
Big Data Book PDF

Author : Kuan-Ching Li,Hai Jiang,Laurence T. Yang,Alfredo Cuzzocrea
Publisher : CRC Press
Page : 498 pages
File Size : 46,8 Mb
Release : 2015-02-23
Category : Computers
ISBN : 9781482240566

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Big Data by Kuan-Ching Li,Hai Jiang,Laurence T. Yang,Alfredo Cuzzocrea Pdf

As today's organizations are capturing exponentially larger amounts of data than ever, now is the time for organizations to rethink how they digest that data. Through advanced algorithms and analytics techniques, organizations can harness this data, discover hidden patterns, and use the newly acquired knowledge to achieve competitive advantages.Pre

Building Big Data Pipelines with Apache Beam

Jan Lukavsky
Building Big Data Pipelines with Apache Beam Book PDF

Author : Jan Lukavsky
Publisher : Packt Publishing Ltd
Page : 342 pages
File Size : 42,8 Mb
Release : 2022-01-21
Category : Computers
ISBN : 9781800566569

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Building Big Data Pipelines with Apache Beam by Jan Lukavsky Pdf

Implement, run, operate, and test data processing pipelines using Apache Beam Key FeaturesUnderstand how to improve usability and productivity when implementing Beam pipelinesLearn how to use stateful processing to implement complex use cases using Apache BeamImplement, test, and run Apache Beam pipelines with the help of expert tips and techniquesBook Description Apache Beam is an open source unified programming model for implementing and executing data processing pipelines, including Extract, Transform, and Load (ETL), batch, and stream processing. This book will help you to confidently build data processing pipelines with Apache Beam. You'll start with an overview of Apache Beam and understand how to use it to implement basic pipelines. You'll also learn how to test and run the pipelines efficiently. As you progress, you'll explore how to structure your code for reusability and also use various Domain Specific Languages (DSLs). Later chapters will show you how to use schemas and query your data using (streaming) SQL. Finally, you'll understand advanced Apache Beam concepts, such as implementing your own I/O connectors. By the end of this book, you'll have gained a deep understanding of the Apache Beam model and be able to apply it to solve problems. What you will learnUnderstand the core concepts and architecture of Apache BeamImplement stateless and stateful data processing pipelinesUse state and timers for processing real-time event processingStructure your code for reusabilityUse streaming SQL to process real-time data for increasing productivity and data accessibilityRun a pipeline using a portable runner and implement data processing using the Apache Beam Python SDKImplement Apache Beam I/O connectors using the Splittable DoFn APIWho this book is for This book is for data engineers, data scientists, and data analysts who want to learn how Apache Beam works. Intermediate-level knowledge of the Java programming language is assumed.

Big Data Application in Power Systems

Reza Arghandeh,Yuxun Zhou
Big Data Application in Power Systems Book PDF

Author : Reza Arghandeh,Yuxun Zhou
Publisher : Elsevier
Page : 480 pages
File Size : 55,5 Mb
Release : 2017-11-27
Category : Science
ISBN : 9780128119693

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Big Data Application in Power Systems by Reza Arghandeh,Yuxun Zhou Pdf

Big Data Application in Power Systems brings together experts from academia, industry and regulatory agencies who share their understanding and discuss the big data analytics applications for power systems diagnostics, operation and control. Recent developments in monitoring systems and sensor networks dramatically increase the variety, volume and velocity of measurement data in electricity transmission and distribution level. The book focuses on rapidly modernizing monitoring systems, measurement data availability, big data handling and machine learning approaches to process high dimensional, heterogeneous and spatiotemporal data. The book chapters discuss challenges, opportunities, success stories and pathways for utilizing big data value in smart grids. Provides expert analysis of the latest developments by global authorities Contains detailed references for further reading and extended research Provides additional cross-disciplinary lessons learned from broad disciplines such as statistics, computer science and bioinformatics Focuses on rapidly modernizing monitoring systems, measurement data availability, big data handling and machine learning approaches to process high dimensional, heterogeneous and spatiotemporal data

Distributed Computing in Big Data Analytics

Sourav Mazumder,Robin Singh Bhadoria,Ganesh Chandra Deka
Distributed Computing in Big Data Analytics Book PDF

Author : Sourav Mazumder,Robin Singh Bhadoria,Ganesh Chandra Deka
Publisher : Springer
Page : 162 pages
File Size : 51,9 Mb
Release : 2017-08-29
Category : Computers
ISBN : 9783319598345

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Distributed Computing in Big Data Analytics by Sourav Mazumder,Robin Singh Bhadoria,Ganesh Chandra Deka Pdf

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.

Hadoop Application Architectures

Mark Grover,Ted Malaska,Jonathan Seidman,Gwen Shapira
Hadoop Application Architectures Book PDF

Author : Mark Grover,Ted Malaska,Jonathan Seidman,Gwen Shapira
Publisher : "O'Reilly Media, Inc."
Page : 399 pages
File Size : 49,7 Mb
Release : 2015-06-30
Category : Computers
ISBN : 9781491900079

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Hadoop Application Architectures by Mark Grover,Ted Malaska,Jonathan Seidman,Gwen Shapira Pdf

Get expert guidance on architecting end-to-end data management solutions with Apache Hadoop. While many sources explain how to use various components in the Hadoop ecosystem, this practical book takes you through architectural considerations necessary to tie those components together into a complete tailored application, based on your particular use case. To reinforce those lessons, the book’s second section provides detailed examples of architectures used in some of the most commonly found Hadoop applications. Whether you’re designing a new Hadoop application, or planning to integrate Hadoop into your existing data infrastructure, Hadoop Application Architectures will skillfully guide you through the process. This book covers: Factors to consider when using Hadoop to store and model data Best practices for moving data in and out of the system Data processing frameworks, including MapReduce, Spark, and Hive Common Hadoop processing patterns, such as removing duplicate records and using windowing analytics Giraph, GraphX, and other tools for large graph processing on Hadoop Using workflow orchestration and scheduling tools such as Apache Oozie Near-real-time stream processing with Apache Storm, Apache Spark Streaming, and Apache Flume Architecture examples for clickstream analysis, fraud detection, and data warehousing

Practical Big Data Analytics

Nataraj Dasgupta
Practical Big Data Analytics Book PDF

Author : Nataraj Dasgupta
Publisher : Packt Publishing Ltd
Page : 402 pages
File Size : 48,9 Mb
Release : 2018-01-15
Category : Computers
ISBN : 9781783554409

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Practical Big Data Analytics by Nataraj Dasgupta Pdf

Get command of your organizational Big Data using the power of data science and analytics Key Features A perfect companion to boost your Big Data storing, processing, analyzing skills to help you take informed business decisions Work with the best tools such as Apache Hadoop, R, Python, and Spark for NoSQL platforms to perform massive online analyses Get expert tips on statistical inference, machine learning, mathematical modeling, and data visualization for Big Data Book Description Big Data analytics relates to the strategies used by organizations to collect, organize and analyze large amounts of data to uncover valuable business insights that otherwise cannot be analyzed through traditional systems. Crafting an enterprise-scale cost-efficient Big Data and machine learning solution to uncover insights and value from your organization's data is a challenge. Today, with hundreds of new Big Data systems, machine learning packages and BI Tools, selecting the right combination of technologies is an even greater challenge. This book will help you do that. With the help of this guide, you will be able to bridge the gap between the theoretical world of technology with the practical ground reality of building corporate Big Data and data science platforms. You will get hands-on exposure to Hadoop and Spark, build machine learning dashboards using R and R Shiny, create web-based apps using NoSQL databases such as MongoDB and even learn how to write R code for neural networks. By the end of the book, you will have a very clear and concrete understanding of what Big Data analytics means, how it drives revenues for organizations, and how you can develop your own Big Data analytics solution using different tools and methods articulated in this book. What you will learn - Get a 360-degree view into the world of Big Data, data science and machine learning - Broad range of technical and business Big Data analytics topics that caters to the interests of the technical experts as well as corporate IT executives - Get hands-on experience with industry-standard Big Data and machine learning tools such as Hadoop, Spark, MongoDB, KDB+ and R - Create production-grade machine learning BI Dashboards using R and R Shiny with step-by-step instructions - Learn how to combine open-source Big Data, machine learning and BI Tools to create low-cost business analytics applications - Understand corporate strategies for successful Big Data and data science projects - Go beyond general-purpose analytics to develop cutting-edge Big Data applications using emerging technologies Who this book is for The book is intended for existing and aspiring Big Data professionals who wish to become the go-to person in their organization when it comes to Big Data architecture, analytics, and governance. While no prior knowledge of Big Data or related technologies is assumed, it will be helpful to have some programming experience.

Big Data: Concepts, Methodologies, Tools, and Applications

Management Association, Information Resources
Big Data Concepts Methodologies Tools and Applications Book PDF

Author : Management Association, Information Resources
Publisher : IGI Global
Page : 2478 pages
File Size : 53,7 Mb
Release : 2016-04-20
Category : Computers
ISBN : 9781466698413

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

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

James Warren,Nathan Marz
Big Data Book PDF

Author : James Warren,Nathan Marz
Publisher : Simon and Schuster
Page : 481 pages
File Size : 48,5 Mb
Release : 2015-04-29
Category : Computers
ISBN : 9781638351108

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Big Data by James Warren,Nathan Marz Pdf

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

Modern Big Data Architectures

Dominik Ryzko
Modern Big Data Architectures Book PDF

Author : Dominik Ryzko
Publisher : John Wiley & Sons
Page : 208 pages
File Size : 41,5 Mb
Release : 2020-03-31
Category : Computers
ISBN : 9781119597841

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Modern Big Data Architectures by Dominik Ryzko Pdf

Provides an up-to-date analysis of big data and multi-agent systems The term Big Data refers to the cases, where data sets are too large or too complex for traditional data-processing software. With the spread of new concepts such as Edge Computing or the Internet of Things, production, processing and consumption of this data becomes more and more distributed. As a result, applications increasingly require multiple agents that can work together. A multi-agent system (MAS) is a self-organized computer system that comprises multiple intelligent agents interacting to solve problems that are beyond the capacities of individual agents. Modern Big Data Architectures examines modern concepts and architecture for Big Data processing and analytics. This unique, up-to-date volume provides joint analysis of big data and multi-agent systems, with emphasis on distributed, intelligent processing of very large data sets. Each chapter contains practical examples and detailed solutions suitable for a wide variety of applications. The author, an internationally-recognized expert in Big Data and distributed Artificial Intelligence, demonstrates how base concepts such as agent, actor, and micro-service have reached a point of convergence—enabling next generation systems to be built by incorporating the best aspects of the field. This book: Illustrates how data sets are produced and how they can be utilized in various areas of industry and science Explains how to apply common computational models and state-of-the-art architectures to process Big Data tasks Discusses current and emerging Big Data applications of Artificial Intelligence Modern Big Data Architectures: A Multi-Agent Systems Perspective is a timely and important resource for data science professionals and students involved in Big Data analytics, and machine and artificial learning.

Advanced Optimization Methods and Big Data Applications in Energy Demand Forecast

Federico Divina,Francisco A. Gómez Vela ,Miguel García-Torres
Advanced Optimization Methods and Big Data Applications in Energy Demand Forecast Book PDF

Author : Federico Divina,Francisco A. Gómez Vela ,Miguel García-Torres
Publisher : MDPI
Page : 100 pages
File Size : 52,8 Mb
Release : 2021-08-30
Category : Technology & Engineering
ISBN : 9783036508627

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Advanced Optimization Methods and Big Data Applications in Energy Demand Forecast by Federico Divina,Francisco A. Gómez Vela ,Miguel García-Torres Pdf

The use of data collectors in energy systems is growing more and more. For example, smart sensors are now widely used in energy production and energy consumption systems. This implies that huge amounts of data are generated and need to be analyzed in order to extract useful insights from them. Such big data give rise to a number of opportunities and challenges for informed decision making. In recent years, researchers have been working very actively in order to come up with effective and powerful techniques in order to deal with the huge amount of data available. Such approaches can be used in the context of energy production and consumption considering the amount of data produced by all samples and measurements, as well as including many additional features. With them, automated machine learning methods for extracting relevant patterns, high-performance computing, or data visualization are being successfully applied to energy demand forecasting.

Big Data Applications for Improving Library Services

Dhamdhere, Sangeeta Namdev
Big Data Applications for Improving Library Services Book PDF

Author : Dhamdhere, Sangeeta Namdev
Publisher : IGI Global
Page : 211 pages
File Size : 45,5 Mb
Release : 2020-09-25
Category : Language Arts & Disciplines
ISBN : 9781799830511

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Big Data Applications for Improving Library Services by Dhamdhere, Sangeeta Namdev Pdf

Today, libraries must provide various web-based services, social media, and internet to patrons in order to adequately support their information needs. In addition to these services, the maintenance of online literature, databases, data sets, and archives cause librarians to have to handle huge amounts of data each day. Big data can support with quality improvement and problem solving to improve library services and can help librarians to provide up-to-date and innovative real-time services to library users. Big Data Applications for Improving Library Services is an essential scholarly publication that examines the implications and applications of big data analytics on services provided by libraries. Highlighting a wide range of topics such as data analytics, mobile technologies, and web-based services, this book is ideal for librarians, knowledge managers, data scientists, data analysts, cataloguers, academicians, IT professionals, researchers, and students.