Download or read book Real Time Analytics written by Byron Ellis and published by John Wiley & Sons. This book was released on 2014-06-23 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Construct a robust end-to-end solution for analyzing and visualizing streaming data Real-time analytics is the hottest topic in data analytics today. In Real-Time Analytics: Techniques to Analyze and Visualize Streaming Data, expert Byron Ellis teaches data analysts technologies to build an effective real-time analytics platform. This platform can then be used to make sense of the constantly changing data that is beginning to outpace traditional batch-based analysis platforms. The author is among a very few leading experts in the field. He has a prestigious background in research, development, analytics, real-time visualization, and Big Data streaming and is uniquely qualified to help you explore this revolutionary field. Moving from a description of the overall analytic architecture of real-time analytics to using specific tools to obtain targeted results, Real-Time Analytics leverages open source and modern commercial tools to construct robust, efficient systems that can provide real-time analysis in a cost-effective manner. The book includes: A deep discussion of streaming data systems and architectures Instructions for analyzing, storing, and delivering streaming data Tips on aggregating data and working with sets Information on data warehousing options and techniques Real-Time Analytics includes in-depth case studies for website analytics, Big Data, visualizing streaming and mobile data, and mining and visualizing operational data flows. The book's "recipe" layout lets readers quickly learn and implement different techniques. All of the code examples presented in the book, along with their related data sets, are available on the companion website.

Download or read book Digital Transformation Technology written by Dalia A. Magdi and published by Springer Nature. This book was released on 2021-08-23 with total page 585 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of best-selected research papers presented at the Second World Conference on Internet of Things: Applications & Future (ITAF 2020) organized by Global Knowledge Research Foundation during 16 – 17 December 2020. It includes innovative works from researchers, leading innovators, business executives and industry professionals to examine the latest advances and applications for commercial and industrial end users across sectors within the emerging Internet of things ecosphere. It shares state-of-the-art as well as emerging topics related to Internet of things such as big data research, emerging services and analytics, Internet of things (IoT) fundamentals, electronic computation and analysis, big data for multi-discipline services, security, privacy and trust, IoT technologies and open and cloud technologies.

Download or read book International Conference on Innovative Computing and Communications written by Deepak Gupta and published by Springer Nature. This book was released on 2020-08-01 with total page 1152 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes high-quality research papers presented at the Third International Conference on Innovative Computing and Communication (ICICC 2020), which is held at the Shaheed Sukhdev College of Business Studies, University of Delhi, Delhi, India, on 21–23 February, 2020. Introducing the innovative works of scientists, professors, research scholars, students and industrial experts in the field of computing and communication, the book promotes the transformation of fundamental research into institutional and industrialized research and the conversion of applied exploration into real-time applications.

Download or read book Big Data BigData 2018 written by Francis Y. L. Chin and published by Springer. This book was released on 2018-06-20 with total page 387 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the proceedings of the 7th International Conference on BIGDATA 2018, held as Part of SCF 2018 in Seattle, WA, USA in June 2018. The 22 full papers together with 10 short papers published in this volume were carefully reviewed and selected from 97 submissions. They are organized in topical sections such as Data analysis, data as a service, services computing, data conversion, data storage, data centers, dataflow architectures, data compression, data exchange, data modeling, databases, and data management.

Download or read book Machine Learning for Data Streams written by Albert Bifet and published by MIT Press. This book was released on 2018-03-16 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: A hands-on approach to tasks and techniques in data stream mining and real-time analytics, with examples in MOA, a popular freely available open-source software framework. Today many information sources—including sensor networks, financial markets, social networks, and healthcare monitoring—are so-called data streams, arriving sequentially and at high speed. Analysis must take place in real time, with partial data and without the capacity to store the entire data set. This book presents algorithms and techniques used in data stream mining and real-time analytics. Taking a hands-on approach, the book demonstrates the techniques using MOA (Massive Online Analysis), a popular, freely available open-source software framework, allowing readers to try out the techniques after reading the explanations. The book first offers a brief introduction to the topic, covering big data mining, basic methodologies for mining data streams, and a simple example of MOA. More detailed discussions follow, with chapters on sketching techniques, change, classification, ensemble methods, regression, clustering, and frequent pattern mining. Most of these chapters include exercises, an MOA-based lab session, or both. Finally, the book discusses the MOA software, covering the MOA graphical user interface, the command line, use of its API, and the development of new methods within MOA. The book will be an essential reference for readers who want to use data stream mining as a tool, researchers in innovation or data stream mining, and programmers who want to create new algorithms for MOA.

Download or read book Learning Spark written by Jules S. Damji and published by O'Reilly Media. This book was released on 2020-07-16 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data is bigger, arrives faster, and comes in a variety of formats—and it all needs to be processed at scale for analytics or machine learning. But how can you process such varied workloads efficiently? Enter Apache Spark. Updated to include Spark 3.0, this second edition shows data engineers and data scientists why structure and unification in Spark matters. Specifically, this book explains how to perform simple and complex data analytics and employ machine learning algorithms. Through step-by-step walk-throughs, code snippets, and notebooks, you’ll be able to: Learn Python, SQL, Scala, or Java high-level Structured APIs Understand Spark operations and SQL Engine Inspect, tune, and debug Spark operations with Spark configurations and Spark UI Connect to data sources: JSON, Parquet, CSV, Avro, ORC, Hive, S3, or Kafka Perform analytics on batch and streaming data using Structured Streaming Build reliable data pipelines with open source Delta Lake and Spark Develop machine learning pipelines with MLlib and productionize models using MLflow

Download or read book Real Time Big Data Analytics written by Sumit Gupta and published by Packt Publishing Ltd. This book was released on 2016-02-26 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: Design, process, and analyze large sets of complex data in real time About This Book Get acquainted with transformations and database-level interactions, and ensure the reliability of messages processed using Storm Implement strategies to solve the challenges of real-time data processing Load datasets, build queries, and make recommendations using Spark SQL Who This Book Is For If you are a Big Data architect, developer, or a programmer who wants to develop applications/frameworks to implement real-time analytics using open source technologies, then this book is for you. What You Will Learn Explore big data technologies and frameworks Work through practical challenges and use cases of real-time analytics versus batch analytics Develop real-word use cases for processing and analyzing data in real-time using the programming paradigm of Apache Storm Handle and process real-time transactional data Optimize and tune Apache Storm for varied workloads and production deployments Process and stream data with Amazon Kinesis and Elastic MapReduce Perform interactive and exploratory data analytics using Spark SQL Develop common enterprise architectures/applications for real-time and batch analytics In Detail Enterprise has been striving hard to deal with the challenges of data arriving in real time or near real time. Although there are technologies such as Storm and Spark (and many more) that solve the challenges of real-time data, using the appropriate technology/framework for the right business use case is the key to success. This book provides you with the skills required to quickly design, implement and deploy your real-time analytics using real-world examples of big data use cases. From the beginning of the book, we will cover the basics of varied real-time data processing frameworks and technologies. We will discuss and explain the differences between batch and real-time processing in detail, and will also explore the techniques and programming concepts using Apache Storm. Moving on, we'll familiarize you with “Amazon Kinesis” for real-time data processing on cloud. We will further develop your understanding of real-time analytics through a comprehensive review of Apache Spark along with the high-level architecture and the building blocks of a Spark program. You will learn how to transform your data, get an output from transformations, and persist your results using Spark RDDs, using an interface called Spark SQL to work with Spark. At the end of this book, we will introduce Spark Streaming, the streaming library of Spark, and will walk you through the emerging Lambda Architecture (LA), which provides a hybrid platform for big data processing by combining real-time and precomputed batch data to provide a near real-time view of incoming data. Style and approach This step-by-step is an easy-to-follow, detailed tutorial, filled with practical examples of basic and advanced features. Each topic is explained sequentially and supported by real-world examples and executable code snippets.

Download or read book Building Data Streaming Applications with Apache Kafka written by Manish Kumar and published by Packt Publishing Ltd. This book was released on 2017-08-18 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: Design and administer fast, reliable enterprise messaging systems with Apache Kafka About This Book Build efficient real-time streaming applications in Apache Kafka to process data streams of data Master the core Kafka APIs to set up Apache Kafka clusters and start writing message producers and consumers A comprehensive guide to help you get a solid grasp of the Apache Kafka concepts in Apache Kafka with pracitcalpractical examples Who This Book Is For If you want to learn how to use Apache Kafka and the different tools in the Kafka ecosystem in the easiest possible manner, this book is for you. Some programming experience with Java is required to get the most out of this book What You Will Learn Learn the basics of Apache Kafka from scratch Use the basic building blocks of a streaming application Design effective streaming applications with Kafka using Spark, Storm &, and Heron Understand the importance of a low -latency , high- throughput, and fault-tolerant messaging system Make effective capacity planning while deploying your Kafka Application Understand and implement the best security practices In Detail Apache Kafka is a popular distributed streaming platform that acts as a messaging queue or an enterprise messaging system. It lets you publish and subscribe to a stream of records, and process them in a fault-tolerant way as they occur. This book is a comprehensive guide to designing and architecting enterprise-grade streaming applications using Apache Kafka and other big data tools. It includes best practices for building such applications, and tackles some common challenges such as how to use Kafka efficiently and handle high data volumes with ease. This book first takes you through understanding the type messaging system and then provides a thorough introduction to Apache Kafka and its internal details. The second part of the book takes you through designing streaming application using various frameworks and tools such as Apache Spark, Apache Storm, and more. Once you grasp the basics, we will take you through more advanced concepts in Apache Kafka such as capacity planning and security. By the end of this book, you will have all the information you need to be comfortable with using Apache Kafka, and to design efficient streaming data applications with it. Style and approach A step-by –step, comprehensive guide filled with practical and real- world examples

Download or read book Streaming Data written by Andrew Psaltis and published by Simon and Schuster. This book was released on 2017-05-31 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Streaming Data introduces the concepts and requirements of streaming and real-time data systems. The book is an idea-rich tutorial that teaches you to think about how to efficiently interact with fast-flowing data. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology As humans, we're constantly filtering and deciphering the information streaming toward us. In the same way, streaming data applications can accomplish amazing tasks like reading live location data to recommend nearby services, tracking faults with machinery in real time, and sending digital receipts before your customers leave the shop. Recent advances in streaming data technology and techniques make it possible for any developer to build these applications if they have the right mindset. This book will let you join them. About the Book Streaming Data is an idea-rich tutorial that teaches you to think about efficiently interacting with fast-flowing data. Through relevant examples and illustrated use cases, you'll explore designs for applications that read, analyze, share, and store streaming data. Along the way, you'll discover the roles of key technologies like Spark, Storm, Kafka, Flink, RabbitMQ, and more. This book offers the perfect balance between big-picture thinking and implementation details. What's Inside The right way to collect real-time data Architecting a streaming pipeline Analyzing the data Which technologies to use and when About the Reader Written for developers familiar with relational database concepts. No experience with streaming or real-time applications required. About the Author Andrew Psaltis is a software engineer focused on massively scalable real-time analytics. Table of Contents PART 1 - A NEW HOLISTIC APPROACH Introducing streaming data Getting data from clients: data ingestion Transporting the data from collection tier: decoupling the data pipeline Analyzing streaming data Algorithms for data analysis Storing the analyzed or collected data Making the data available Consumer device capabilities and limitations accessing the data PART 2 - TAKING IT REAL WORLD Analyzing Meetup RSVPs in real time

Download or read book Proceedings of the XVI International symposium Symorg 2018 written by Nevenka Žarkić-Joksimović and published by University of Belgrade, Faculty of Organizational Sciences . This book was released on 2018-06-12 with total page 1161 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Handbook of Large Scale Distributed Computing in Smart Healthcare written by Samee U. Khan and published by Springer. This book was released on 2017-08-07 with total page 630 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume offers readers various perspectives and visions for cutting-edge research in ubiquitous healthcare. The topics emphasize large-scale architectures and high performance solutions for smart healthcare, healthcare monitoring using large-scale computing techniques, Internet of Things (IoT) and big data analytics for healthcare, Fog Computing, mobile health, large-scale medical data mining, advanced machine learning methods for mining multidimensional sensor data, smart homes, and resource allocation methods for the BANs. The book contains high quality chapters contributed by leading international researchers working in domains, such as e-Health, pervasive and context-aware computing, cloud, grid, cluster, and big-data computing. We are optimistic that the topics included in this book will provide a multidisciplinary research platform to the researchers, practitioners, and students from biomedical engineering, health informatics, computer science, and computer engineering.

Download or read book Mastering Data Storage and Processing written by Cybellium Ltd and published by Cybellium Ltd. This book was released on with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlock the Power of Effective Data Storage and Processing with "Mastering Data Storage and Processing" In today's data-driven world, the ability to store, manage, and process data effectively is the cornerstone of success. "Mastering Data Storage and Processing" is your definitive guide to mastering the art of seamlessly managing and processing data for optimal performance and insights. Whether you're an experienced data professional or a newcomer to the realm of data management, this book equips you with the knowledge and skills needed to navigate the intricacies of modern data storage and processing. About the Book: "Mastering Data Storage and Processing" takes you on an enlightening journey through the intricacies of data storage and processing, from foundational concepts to advanced techniques. From storage systems to data pipelines, this book covers it all. Each chapter is meticulously designed to provide both a deep understanding of the concepts and practical applications in real-world scenarios. Key Features: · Foundational Principles: Build a strong foundation by understanding the core principles of data storage technologies, file systems, and data processing paradigms. · Storage Systems: Explore a range of data storage systems, from relational databases and NoSQL databases to cloud-based storage solutions, understanding their strengths and applications. · Data Modeling and Design: Learn how to design effective data schemas, optimize storage structures, and establish relationships for efficient data organization. · Data Processing Paradigms: Dive into various data processing paradigms, including batch processing, stream processing, and real-time analytics, for extracting valuable insights. · Big Data Technologies: Master the essentials of big data technologies such as Hadoop, Spark, and distributed computing frameworks for processing massive datasets. · Data Pipelines: Understand the design and implementation of data pipelines for data ingestion, transformation, and loading, ensuring seamless data flow. · Scalability and Performance: Discover strategies for optimizing data storage and processing systems for scalability, fault tolerance, and high performance. · Real-World Use Cases: Gain insights from real-world examples across industries, from finance and healthcare to e-commerce and beyond. · Data Security and Privacy: Explore best practices for data security, encryption, access control, and compliance to protect sensitive information. Who This Book Is For: "Mastering Data Storage and Processing" is designed for data engineers, developers, analysts, and anyone passionate about effective data management. Whether you're aiming to enhance your skills or embark on a journey toward becoming a data management expert, this book provides the insights and tools to navigate the complexities of data storage and processing. © 2023 Cybellium Ltd. All rights reserved. www.cybellium.com

Download or read book Urban Analytics with Social Media Data written by Tan Yigitcanlar and published by CRC Press. This book was released on 2022-07-20 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: The use of data science and urban analytics has become a defining feature of smart cities. This timely book is a clear guide to the use of social media data for urban analytics. The book presents the foundations of urban analytics with social media data, along with real-world applications and insights on the platforms we use today. It looks at social media analytics platforms, cyberphysical data analytics platforms, crowd detection platforms, City-as-a-Platform, and city-as-a-sensor for platform urbanism. The book provides examples to illustrate how we apply and analyse social media data to determine disaster severity, assist authorities with pandemic policy, and capture public perception of smart cities. This will be a useful reference for those involved with and researching social, data, and urban analytics and informatics.

Download or read book Computing and Communications Engineering in Real Time Application Development written by B. K. Mishra and published by CRC Press. This book was released on 2022-09-22 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Experts in research, industry, and academia cover recent trends and state-of-the art solutions in computer and communications engineering, focusing specifically on real-time applications of electronics, communications, computing, and information technology. The volume provides sound theoretical and application-oriented knowledge with a special focus on the development of safety-critical networks and integrated electrical and electronics systems. The volume also features numerous new algorithms that assist in solving computer and communication engineering problems.

Download or read book Proceedings of 4th International Conference on Frontiers in Computing and Systems written by Dipak Kumar Kole and published by Springer Nature. This book was released on with total page 728 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Multimedia Big Data Computing for IoT Applications written by Sudeep Tanwar and published by Springer. This book was released on 2019-07-17 with total page 477 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book considers all aspects of managing the complexity of Multimedia Big Data Computing (MMBD) for IoT applications and develops a comprehensive taxonomy. It also discusses a process model that addresses a number of research challenges associated with MMBD, such as scalability, accessibility, reliability, heterogeneity, and Quality of Service (QoS) requirements, presenting case studies to demonstrate its application. Further, the book examines the layered architecture of MMBD computing and compares the life cycle of both big data and MMBD. Written by leading experts, it also includes numerous solved examples, technical descriptions, scenarios, procedures, and algorithms.

Download or read book Big Data Processing with Apache Spark written by Srini Penchikala and published by Lulu.com. This book was released on 2018-03-13 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt: Apache Spark is a popular open-source big-data processing framework thatÕs built around speed, ease of use, and unified distributed computing architecture. Not only it supports developing applications in different languages like Java, Scala, Python, and R, itÕs also hundred times faster in memory and ten times faster even when running on disk compared to traditional data processing frameworks. Whether you are currently working on a big data project or interested in learning more about topics like machine learning, streaming data processing, and graph data analytics, this book is for you. You can learn about Apache Spark and develop Spark programs for various use cases in big data analytics using the code examples provided. This book covers all the libraries in Spark ecosystem: Spark Core, Spark SQL, Spark Streaming, Spark ML, and Spark GraphX.