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Item #:
156902045
Scalable Big Data Architecture: A Practitioners Guide to Choosing Relevant Big Data Architecture, (Paperback)
92% of respondents would recommend this to a friend
Item #:
156902045
SLE 1390
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Scalable Big Data Architecture is your essential guide to navigating the complexities of Big Data with practical examples and proven methodologies.
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What Stands Out
Comprehensive Guidance
Offers detailed insights into selecting the appropriate Big Data architecture, catering to both beginners and experienced practitioners, ensuring informed decision-making for various project requirements.
Practical Frameworks
Presents actionable frameworks and examples, enabling readers to apply theoretical concepts to real-world scenarios, enhancing the practicality of Big Data implementation.
Up-to-Date Insights
Incorporates the latest trends and technologies in Big Data, providing readers with a competitive edge when adapting their architectures to future developments and scalability needs.
Product Details
- 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.
| Book format | Paperback |
| Fiction/nonfiction | Non-Fiction |
| Genre | Computing & Internet |
| Publication date | December, 2015 |
| Pages | 141 |
| Subgenre | Data Science |
| Series title | No Series |
| Edition | 1 |
| Publisher | Apress |
| Original languages | English |
| Language | English |
| Is collectible | N |
| Recording time | 0 min |
| Retail packaging | Single Piece |
| Assembled product dimensions (l x w x h) | 7.00 x 0.34 x 10.00 in (17.8 x 0.9 x 25.4 cm) |
| Assembled product weight | 0.64 lb (290 grams) |
| Bisac subject heading | Computers |
Who Should Buy?
-
Data Engineers
Provides essential insights on designing scalable architecture, essential for data engineers working on large-scale data systems.
-
IT Architects
IT architects will benefit from understanding various big data architectures for effective system design and integration.
-
Business Analysts
Business analysts looking to leverage big data can gain valuable knowledge to interpret architectures effectively for business insights.
-
Beginners in Data
Individuals new to data concepts may find the technical terminology overwhelming without prior foundational knowledge.
Product Description
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Bahaaldine Azarmi All Books Editorial Review
Scalable Big Data Architecture: A Practitioners Guide to Choosing Relevant Big Data Architecture (Paperback) is a non-fiction book that caters to readers interested in computing and internet technologies. Published in December 2015 by Apress, this 141-page guide delves into the intricacies of big data architecture, making complex concepts accessible to practitioners in the field. The paperback format ensures it's easy to handle, and the dimensions of 7.00 x 0.34 x 10.00 inches make it convenient for both reading and storage. This book serves as a valuable resource for data scientists and IT professionals looking to deepen their knowledge and skills in big data management. Readers have found it enlightening for making informed choices regarding big data architecture, contributing positively to their expertise.
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Pros
- Concise overview of big data architecture
- Valuable insights for data science practitioners
- User-friendly format and layout
- Applicable real-world examples provided
- Suitable for both beginners and experts
Cons
- Limited topics due to concise nature of the book
Product Price History
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SLE 1390
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Features & Benefits
- Comprehensive guide to various big data architectures.
- Covers real-world use cases using No-SQL databases.
- Demonstrates scalable data processing methods and technologies.
- Integrates machine learning and stream analytics seamlessly.
- Practical examples using tools like Logstash, Spark, and Kafka.
- Ideal for developers, data architects, and data scientists.
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