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Scalable Big Data Architecture - by  Bahaaldine Azarmi (Paperback) - 1 of 1

Scalable Big Data Architecture - by Bahaaldine Azarmi (Paperback)

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Highlights

  • This book highlights the different types of data architecture and illustrates the many possibilities hidden behind the term "Big Data", from the usage of No-SQL databases to the deployment of stream analytics architecture, machine learning, and governance.
  • About the Author: Bahaaldine Azarmi is the co-founder and CTO of reach five, a Social Data Marketing Platform.
  • 141 Pages
  • Computers + Internet,

Description



Book Synopsis



This book highlights the different types of data architecture and illustrates the many possibilities hidden behind the term "Big Data", from the usage of No-SQL databases to the deployment of stream analytics architecture, machine learning, and governance.

Scalable Big Data Architecture covers real-world, concrete industry use cases that leverage complex distributed applications, which involve web applications, RESTful API, and high throughput of large amount of data stored in highly scalable No-SQL data stores such as Couchbase and Elasticsearch. This book demonstrates how data processing can be done at scale from the usage of NoSQL datastores to the combination of Big Data distribution.

When the data processing is too complex and involves different processing topology like long running jobs, stream processing, multiple data sources correlation, and machine learning, it's often necessary to delegate the load to Hadoop or Spark and use the No-SQLto serve processed data in real time.

This book shows you how to choose a relevant combination of big data technologies available within the Hadoop ecosystem. It focuses on processing long jobs, architecture, stream data patterns, log analysis, and real time analytics. Every pattern is illustrated with practical examples, which use the different open sourceprojects such as Logstash, Spark, Kafka, and so on.

Traditional data infrastructures are built for digesting and rendering data synthesis and analytics from large amount of data. This book helps you to understand why you should consider using machine learning algorithms early on in the project, before being overwhelmed by constraints imposed by dealing with the high throughput of Big data.

Scalable Big Data Architecture is for developers, data architects, and data scientists looking for a better understanding of how to choose the most relevant pattern for a Big Data project and which tools tointegrate into that pattern.



About the Author



Bahaaldine Azarmi is the co-founder and CTO of reach five, a Social Data Marketing Platform. Bahaaldine has a strong background and expertise skills in REST API and Big Data architecture. Prior to founding reach five, Bahaaldine worked as a technical architect & evangelist for large software vendors such as Oracle & Talend.

He has a master's degree of computer science from Polytech'Paris engineering school, Paris.
Dimensions (Overall): 10.0 Inches (H) x 7.0 Inches (W) x .34 Inches (D)
Weight: .64 Pounds
Suggested Age: 22 Years and Up
Number of Pages: 141
Genre: Computers + Internet
Publisher: Apress
Theme: General
Format: Paperback
Author: Bahaaldine Azarmi
Language: English
Street Date: December 30, 2015
TCIN: 1011988720
UPC: 9781484213278
Item Number (DPCI): 247-13-1393
Origin: Made in the USA or Imported
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Estimated ship dimensions: 0.34 inches length x 7 inches width x 10 inches height
Estimated ship weight: 0.64 pounds
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Q: What topics are covered in this book about Big Data?

submitted by AI Shopping Assistant - 2 days ago
  • A: The book covers data architecture types, No-SQL databases, stream analytics, machine learning, and governance.

    submitted byAI Shopping Assistant - 2 days ago
    Ai generated

Q: Who is the author of this book?

submitted by AI Shopping Assistant - 2 days ago
  • A: The author is Bahaaldine Azarmi, co-founder and CTO of reach five.

    submitted byAI Shopping Assistant - 2 days ago
    Ai generated

Q: What is the significance of machine learning in this book?

submitted by AI Shopping Assistant - 2 days ago
  • A: The book emphasizes using machine learning algorithms early in projects to manage Big Data complexities.

    submitted byAI Shopping Assistant - 2 days ago
    Ai generated

Q: What is the target audience for this book?

submitted by AI Shopping Assistant - 2 days ago
  • A: The book is aimed at developers, data architects, and data scientists interested in Big Data.

    submitted byAI Shopping Assistant - 2 days ago
    Ai generated

Q: What practical examples are included in the book?

submitted by AI Shopping Assistant - 2 days ago
  • A: It includes examples using open source projects like Logstash, Spark, and Kafka for data processing.

    submitted byAI Shopping Assistant - 2 days ago
    Ai generated

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