Streaming Data
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Streaming Data
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Author : Andrew Psaltis
language : en
Publisher: Simon and Schuster
Release Date : 2017-05-31
Streaming Data written by Andrew Psaltis and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-31 with Computers categories.
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
Streaming Systems
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Author : Tyler Akidau
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2018-07-16
Streaming Systems written by Tyler Akidau and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-16 with Computers categories.
Streaming data is a big deal in big data these days. As more and more businesses seek to tame the massive unbounded data sets that pervade our world, streaming systems have finally reached a level of maturity sufficient for mainstream adoption. With this practical guide, data engineers, data scientists, and developers will learn how to work with streaming data in a conceptual and platform-agnostic way. Expanded from Tyler Akidau’s popular blog posts "Streaming 101" and "Streaming 102", this book takes you from an introductory level to a nuanced understanding of the what, where, when, and how of processing real-time data streams. You’ll also dive deep into watermarks and exactly-once processing with co-authors Slava Chernyak and Reuven Lax. You’ll explore: How streaming and batch data processing patterns compare The core principles and concepts behind robust out-of-order data processing How watermarks track progress and completeness in infinite datasets How exactly-once data processing techniques ensure correctness How the concepts of streams and tables form the foundations of both batch and streaming data processing The practical motivations behind a powerful persistent state mechanism, driven by a real-world example How time-varying relations provide a link between stream processing and the world of SQL and relational algebra
Streaming Data Mesh
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Author : Hubert Dulay
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2023-05-11
Streaming Data Mesh written by Hubert Dulay and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-11 with Computers categories.
Data lakes and warehouses have become increasingly fragile, costly, and difficult to maintain as data gets bigger and moves faster. Data meshes can help your organization decentralize data, giving ownership back to the engineers who produced it. This book provides a concise yet comprehensive overview of data mesh patterns for streaming and real-time data services. Authors Hubert Dulay and Stephen Mooney examine the vast differences between streaming and batch data meshes. Data engineers, architects, data product owners, and those in DevOps and MLOps roles will learn steps for implementing a streaming data mesh, from defining a data domain to building a good data product. Through the course of the book, you'll create a complete self-service data platform and devise a data governance system that enables your mesh to work seamlessly. With this book, you will: Design a streaming data mesh using Kafka Learn how to identify a domain Build your first data product using self-service tools Apply data governance to the data products you create Learn the differences between synchronous and asynchronous data services Implement self-services that support decentralized data
Visualizing Streaming Data
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Author : Anthony Aragues
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2018-06-01
Visualizing Streaming Data written by Anthony Aragues and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-01 with Computers categories.
While tools for analyzing streaming and real-time data are gaining adoption, the ability to visualize these data types has yet to catch up. Dashboards are good at conveying daily or weekly data trends at a glance, though capturing snapshots when data is transforming from moment to moment is more difficult—but not impossible. With this practical guide, application designers, data scientists, and system administrators will explore ways to create visualizations that bring context and a sense of time to streaming text data. Author Anthony Aragues guides you through the concepts and tools you need to build visualizations for analyzing data as it arrives. Determine your company’s goals for visualizing streaming data Identify key data sources and learn how to stream them Learn practical methods for processing streaming data Build a client application for interacting with events, logs, and records Explore common components for visualizing streaming data Consider analysis concepts for developing your visualization Define the dashboard’s layout, flow direction, and component movement Improve visualization quality and productivity through collaboration Explore use cases including security, IoT devices, and application data
Real Time Analytics
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Author : Byron Ellis
language : en
Publisher: John Wiley & Sons
Release Date : 2014-06-23
Real Time Analytics written by Byron Ellis and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-23 with Computers categories.
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.
Visualizing Streaming Data
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Author : Anthony Aragues
language : en
Publisher: O'Reilly Media
Release Date : 2018
Visualizing Streaming Data written by Anthony Aragues and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Big data categories.
While tools for analyzing streaming and real-time data are gaining adoption, the ability to visualize these data types has yet to catch up. Dashboards are good at conveying daily or weekly data trends at a glance, though capturing snapshots when data is transforming from moment to moment is more difficult--but not impossible. With this practical guide, application designers, data scientists, and system administrators will explore ways to create visualizations that bring context and a sense of time to streaming text data. Author Anthony Aragues guides you through the concepts and tools you need to build visualizations for analyzing data as it arrives. Determine your company's goals for visualizing streaming data Identify key data sources and learn how to stream them Learn practical methods for processing streaming data Build a client application for interacting with events, logs, and records Explore common components for visualizing streaming data Consider analysis concepts for developing your visualization Define the dashboard's layout, flow direction, and component movement Improve visualization quality and productivity through collaboration Explore use cases including security, IoT devices, and application data
Streaming Sharing Stealing
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Author : Michael D. Smith
language : en
Publisher: MIT Press
Release Date : 2016-08-05
Streaming Sharing Stealing written by Michael D. Smith and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-05 with Business & Economics categories.
How big data is transforming the creative industries, and how those industries can use lessons from Netflix, Amazon, and Apple to fight back. “[The authors explain] gently yet firmly exactly how the internet threatens established ways and what can and cannot be done about it. Their book should be required for anyone who wishes to believe that nothing much has changed.” —The Wall Street Journal “Packed with examples, from the nimble-footed who reacted quickly to adapt their businesses, to laggards who lost empires.” —Financial Times Traditional network television programming has always followed the same script: executives approve a pilot, order a trial number of episodes, and broadcast them, expecting viewers to watch a given show on their television sets at the same time every week. But then came Netflix's House of Cards. Netflix gauged the show's potential from data it had gathered about subscribers' preferences, ordered two seasons without seeing a pilot, and uploaded the first thirteen episodes all at once for viewers to watch whenever they wanted on the devices of their choice. In this book, Michael Smith and Rahul Telang, experts on entertainment analytics, show how the success of House of Cards upended the film and TV industries—and how companies like Amazon and Apple are changing the rules in other entertainment industries, notably publishing and music. We're living through a period of unprecedented technological disruption in the entertainment industries. Just about everything is affected: pricing, production, distribution, piracy. Smith and Telang discuss niche products and the long tail, product differentiation, price discrimination, and incentives for users not to steal content. To survive and succeed, businesses have to adapt rapidly and creatively. Smith and Telang explain how. How can companies discover who their customers are, what they want, and how much they are willing to pay for it? Data. The entertainment industries, must learn to play a little “moneyball.” The bottom line: follow the data.
Machine Learning For Streaming Data With Python
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Author : Joos Korstanje
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-07-15
Machine Learning For Streaming Data With Python written by Joos Korstanje and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-15 with Computers categories.
Apply machine learning to streaming data with the help of practical examples, and deal with challenges that surround streaming Key Features • Work on streaming use cases that are not taught in most data science courses • Gain experience with state-of-the-art tools for streaming data • Mitigate various challenges while handling streaming data Book Description Streaming data is the new top technology to watch out for in the field of data science and machine learning. As business needs become more demanding, many use cases require real-time analysis as well as real-time machine learning. This book will help you to get up to speed with data analytics for streaming data and focus strongly on adapting machine learning and other analytics to the case of streaming data. You will first learn about the architecture for streaming and real-time machine learning. Next, you will look at the state-of-the-art frameworks for streaming data like River. Later chapters will focus on various industrial use cases for streaming data like Online Anomaly Detection and others. As you progress, you will discover various challenges and learn how to mitigate them. In addition to this, you will learn best practices that will help you use streaming data to generate real-time insights. By the end of this book, you will have gained the confidence you need to stream data in your machine learning models. What you will learn • Understand the challenges and advantages of working with streaming data • Develop real-time insights from streaming data • Understand the implementation of streaming data with various use cases to boost your knowledge • Develop a PCA alternative that can work on real-time data • Explore best practices for handling streaming data that you absolutely need to remember • Develop an API for real-time machine learning inference Who this book is for This book is for data scientists and machine learning engineers who have a background in machine learning, are practice and technology-oriented, and want to learn how to apply machine learning to streaming data through practical examples with modern technologies. Although an understanding of basic Python and machine learning concepts is a must, no prior knowledge of streaming is required.
Streaming Linked Data
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Author : Riccardo Tommasini
language : en
Publisher: Springer Nature
Release Date : 2023-01-25
Streaming Linked Data written by Riccardo Tommasini and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-25 with Computers categories.
This book provides a comprehensive overview of core concepts and technological foundations for continuous engineering of Web streams. It presents various systems and applications and includes real-world examples. Last not least, it introduces the readers to RSP4J, a novel open-source project that aims to gather community efforts in software engineering and empirical research. The book starts with an introductory chapter that positions the work by explaining what motivates the design of specific techniques for processing data streams using Web technologies. Chapter 2 briefly summarizes the necessary background concepts and models needed to understand the remaining content of the book. Subsequently, chapter 3 focuses on processing RDF streams, taming data velocity in an open environment characterized by high data variety. It introduces query answering algorithms with RSP-QL and analytics functions over streaming data. Chapter 4 presents the life cycle of streaming linked data, it focuses on publishing streams on the Web as a prerequisite aspect to make data findable and accessible for applications. Chapter 5 touches on the problems of benchmarks and systems that analyze Web streams to foster technological progress. It surveys existing benchmarks and introduces guidelines that may support new practitioners in approaching the issue of continuous analytics. Finally, chapter 6 presents a list of examples and exercises that will help the reader to approach the area, get used to its practices and become confident in its technological possibilities. Overall, this book is mainly written for graduate students and researchers in Web and stream data management. It collects research results and will guide the next generation of researchers and practitioners.
Advanced Real Time Data Integration Apache Kafka And Spark Streaming Techniques
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Author : Adam Jones
language : en
Publisher: Walzone Press
Release Date : 2025-01-03
Advanced Real Time Data Integration Apache Kafka And Spark Streaming Techniques written by Adam Jones and has been published by Walzone Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-03 with Computers categories.
Unlock the potential of cutting-edge real-time data processing with "Advanced Real-Time Data Integration: Apache Kafka and Spark Streaming Techniques." This comprehensive guide serves as your gateway to mastering two pivotal technologies in the world of data integration. Perfect for software developers, data engineers, IT professionals, and students eager to explore the nuances of real-time data, this book equips you with the knowledge to build scalable, efficient, and reliable streaming applications. Delve into the sophisticated architecture of Apache Kafka, understanding its core components and advanced features that make it an essential element of contemporary data infrastructure. Examine the powerful capabilities of Spark Streaming, from foundational concepts to advanced performance optimizations, and discover how to integrate it effortlessly with Kafka to create dynamic data processing solutions. Covering a broad range of topics such as designing robust streaming applications, data serialization, system monitoring, and practical case studies, this book furnishes you with the necessary tools and insights to excel with streaming data. Through clear and concise explanations, "Advanced Real-Time Data Integration: Apache Kafka and Spark Streaming Techniques" simplifies the complexities of these technologies, making them accessible to a wide audience intent on harnessing the full potential of real-time data integration in their projects and enterprises.