Real Time Analytics

Author: Byron Ellis
Publisher: John Wiley & Sons
ISBN: 1118838025
Size: 19.60 MB
Format: PDF, ePub, Mobi
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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.

Real Time Analytics

Author: Byron Ellis
Publisher: John Wiley & Sons
ISBN: 1118837916
Size: 65.89 MB
Format: PDF, Mobi
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Data expert Byron Ellis teaches data analysts new technologies to build an effective real-time analytics platform. The book leverages open source and modern commercial tools to show readers how to construct robust, efficient systems that provide real-time analysis in a cost effective manner.

Real Time Analytics

Author: Byron Ellis
Publisher: John Wiley & Sons
ISBN: 1118837932
Size: 25.91 MB
Format: PDF, ePub, Docs
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Fundamentals Of Stream Processing

Author: Henrique C. M. Andrade
Publisher: Cambridge University Press
ISBN: 1107015545
Size: 71.37 MB
Format: PDF, Docs
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This book teaches fundamentals of stream processing, covering application design, distributed systems infrastructure, and continuous analytic algorithms.

Knowledge Discovery From Data Streams

Author: Joao Gama
Publisher: CRC Press
ISBN: 1439826129
Size: 72.71 MB
Format: PDF, ePub, Docs
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Since the beginning of the Internet age and the increased use of ubiquitous computing devices, the large volume and continuous flow of distributed data have imposed new constraints on the design of learning algorithms. Exploring how to extract knowledge structures from evolving and time-changing data, Knowledge Discovery from Data Streams presents a coherent overview of state-of-the-art research in learning from data streams. The book covers the fundamentals that are imperative to understanding data streams and describes important applications, such as TCP/IP traffic, GPS data, sensor networks, and customer click streams. It also addresses several challenges of data mining in the future, when stream mining will be at the core of many applications. These challenges involve designing useful and efficient data mining solutions applicable to real-world problems. In the appendix, the author includes examples of publicly available software and online data sets. This practical, up-to-date book focuses on the new requirements of the next generation of data mining. Although the concepts presented in the text are mainly about data streams, they also are valid for different areas of machine learning and data mining.

Real Time Analytics Techniques To Analyze And Visualize Streaming Data

Author: Agustin Attebery
Publisher: Createspace Independent Publishing Platform
ISBN: 9781973739999
Size: 34.54 MB
Format: PDF, Kindle
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Real-time analytics is the hottest topic in data analytics today. In Real-Time Analytics: Techniques to Analyze and Visualize Streaming Data, expert Agustin Attebery 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.

Real Time Analytics With Storm And Cassandra

Author: Shilpi Saxena
Publisher: Packt Publishing Ltd
ISBN: 1784390003
Size: 70.44 MB
Format: PDF, ePub, Docs
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If you want to efficiently use Storm and Cassandra together and excel at developing production-grade, distributed real-time applications, then this book is for you. No prior knowledge of using Storm and Cassandra together is necessary. However, a background in Java is expected.

Applied Predictive Analytics

Author: Dean Abbott
Publisher: John Wiley & Sons
ISBN: 111872769X
Size: 60.11 MB
Format: PDF
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Learn the art and science of predictive analytics — techniques that get results Predictive analytics is what translates big data into meaningful, usable business information. Written by a leading expert in the field, this guide examines the science of the underlying algorithms as well as the principles and best practices that govern the art of predictive analytics. It clearly explains the theory behind predictive analytics, teaches the methods, principles, and techniques for conducting predictive analytics projects, and offers tips and tricks that are essential for successful predictive modeling. Hands-on examples and case studies are included. The ability to successfully apply predictive analytics enables businesses to effectively interpret big data; essential for competition today This guide teaches not only the principles of predictive analytics, but also how to apply them to achieve real, pragmatic solutions Explains methods, principles, and techniques for conducting predictive analytics projects from start to finish Illustrates each technique with hands-on examples and includes as series of in-depth case studies that apply predictive analytics to common business scenarios A companion website provides all the data sets used to generate the examples as well as a free trial version of software Applied Predictive Analytics arms data and business analysts and business managers with the tools they need to interpret and capitalize on big data.

Big Data Analytics With Java

Author: Rajat Mehta
Publisher: Packt Publishing Ltd
ISBN: 1787282198
Size: 34.22 MB
Format: PDF, Docs
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Learn the basics of analytics on big data using Java, machine learning and other big data tools About This Book Acquire real-world set of tools for building enterprise level data science applications Surpasses the barrier of other languages in data science and learn create useful object-oriented codes Extensive use of Java compliant big data tools like apache spark, Hadoop, etc. Who This Book Is For This book is for Java developers who are looking to perform data analysis in production environment. Those who wish to implement data analysis in their Big data applications will find this book helpful. What You Will Learn Start from simple analytic tasks on big data Get into more complex tasks with predictive analytics on big data using machine learning Learn real time analytic tasks Understand the concepts with examples and case studies Prepare and refine data for analysis Create charts in order to understand the data See various real-world datasets In Detail This book covers case studies such as sentiment analysis on a tweet dataset, recommendations on a movielens dataset, customer segmentation on an ecommerce dataset, and graph analysis on actual flights dataset. This book is an end-to-end guide to implement analytics on big data with Java. Java is the de facto language for major big data environments, including Hadoop. This book will teach you how to perform analytics on big data with production-friendly Java. This book basically divided into two sections. The first part is an introduction that will help the readers get acquainted with big data environments, whereas the second part will contain a hardcore discussion on all the concepts in analytics on big data. It will take you from data analysis and data visualization to the core concepts and advantages of machine learning, real-life usage of regression and classification using Naive Bayes, a deep discussion on the concepts of clustering,and a review of simple neural networks on big data using deepLearning4j or plain Java Spark code. This book is a must-have book for Java developers who want to start learning big data analytics and want to use it in the real world. Style and approach The approach of book is to deliver practical learning modules in manageable content. Each chapter is a self-contained unit of a concept in big data analytics. Book will step by step builds the competency in the area of big data analytics. Examples using real world case studies to give ideas of real applications and how to use the techniques mentioned. The examples and case studies will be shown using both theory and code.

Streaming Data

Author: Andrew Psaltis
Publisher: Manning Publications
ISBN: 9781617292286
Size: 10.19 MB
Format: PDF, Mobi
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Many of the technologies discussed in the book - Spark, Storm, Kafka, Impala, RabbitMQ, etc. - are covered individually in other books. Throughout this book, readers will get a clear picture of how these technologies work individually and together, gain insight on how to choose the correct technologies, and discover how to fuse them together to architect a robust system. Streaming Data introduces the concepts and requirements of streaming and real-time data systems. Readers will develop a foundation to understand the challenges and solutions of building in-the-moment data systems before committing to specific technologies. Using lots of diagrams, this book systematically builds up the blueprint for an in-the-moment system concept by concept. This book focuses on the big ideas of streaming and real time data systems rather than the implementation details. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.