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Real-Time Analytics: Techniques to Analyze and Visualize Streaming Data
 
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Real-Time Analytics: Techniques to Analyze and Visualize Streaming Data [Format Kindle]

Byron Ellis

Prix conseillé : EUR 37,08 De quoi s'agit-il ?
Prix éditeur - format imprimé : EUR 29,61
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Descriptions du produit

Présentation de l'éditeur

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.

Quatrième de couverture

A COMPLETE SOLUTION FOR DYNAMIC ANALYSIS OF STREAMING DATA Real–Time Analytics provides a complete end–to–end solution for cost–effective analysis and visualization of streaming data. Beginning with a description of the required analytics ecosystem, the book builds upon that foundation with practical guidance toward the tools and techniques that get targeted results. Outlining best practices for each specific application throughout the discovery life cycle, the approach provides easy–to–follow instructions for implementing the presented tools and techniques. Examples taken from real–world applications highlight the usage of various aspects of data processing from tabulation to visualization and forecasting. Readers will: Understand the components of streaming data systems, including their full capabilities and characteristics Learn the relevant architecture and best practices for analysis and storage of streaming data Develop a system for data aggregation, delivery, and warehousing using open source and commercial tools Learn the implementation and application of advanced algorithms and data structures to streaming applications Decreasing data acquisition costs and increasing connectivity are enabling ever more efficient methods of continuous collection, so why do analysis platforms remain largely batch–based? The tools do exist to efficiently handle streaming data analysis and visualization feasibly in terms of time, maintenance and hardware. This book guides readers through the construction of a robust, cost–efficient system with clear, expert instruction.

Détails sur le produit

  • Format : Format Kindle
  • Taille du fichier : 1721 KB
  • Nombre de pages de l'édition imprimée : 401 pages
  • Pagination - ISBN de l'édition imprimée de référence : 1118837916
  • Editeur : Wiley; Édition : 1 (14 juillet 2014)
  • Vendu par : Amazon Media EU S.à r.l.
  • Langue : Anglais
  • ASIN: B00JUUZQP0
  • Synthèse vocale : Activée
  • X-Ray :
  • Word Wise: Non activé
  • Classement des meilleures ventes d'Amazon: n°88.842 dans la Boutique Kindle (Voir le Top 100 dans la Boutique Kindle)
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Commentaires en ligne

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Commentaires client les plus utiles sur Amazon.com (beta)
Amazon.com: 5.0 étoiles sur 5  2 commentaires
5 internautes sur 6 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 End-to-End Solution that gets you excited about its applications 1 septembre 2014
Par Dave Robertson - Publié sur Amazon.com
Format:Broché|Achat vérifié
Brilliant book, well written and easy to understand. Just wish the examples were written in Ruby rather than JAVA but I cant hold that against the author ;).. The book provides a way of solving a problem with an end-to-end solution. Which allows you to understand one way of solving the problem giving you insights into this new area which really get the gears cranking for ideas to potential applications within your own domain.

Awaiting Byron' next book with eager anticipation!
2 internautes sur 4 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 When you're done reading this, you'll understand what Real-Time analytics is about, and the modern-day tools to get you going .. 19 septembre 2014
Par nyceyes - Publié sur Amazon.com
Format:Broché|Achat vérifié
'Wiley', are you listening? =:)

I do a lot of Real-Time work, so this hardy applause comes with experience.

There's a lot of piecemeal content out there which, yes, one can cobble together over time. But for an experienced person to *sequence* an audience through a subject with a bigger, end-to-end solutions point of view in mind -- which is what Byron Ellis' book does for the Real-Time use case -- is a **totally different value proposition**. Speaking from personal experience, it takes a HUGE amount of time, commitment, financial investment in a mini-laboratory (etc.) to constantly tinker with and learn this fast evolving ecosystem towards some practical end. And this is precisely why the cobble-it-together approach doesn't work for many people: It takes stamina, focus, tenacity, and dedication.

Byron coalesced this information in this book.

Take any section, say, Kafka. I know (as a writer) that his stepping people through it's configuration directives was not fun, but he did it because he understood that Kafka alone wasn't enough. He wanted the audience to understand the trade-offs that needed to be considered. And also, beyond being just another message broker, how Kafka could be thought of as a structured persistence layer in and or itself.

You'll see more of what I mean in this well-executed book. Well worth the price.
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