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Architectural Patterns

Architectural Patterns

By : Murali, Pethuru Raj, J, Pethuru Raj Chelliah
2.4 (5)
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Architectural Patterns

Architectural Patterns

2.4 (5)
By: Murali, Pethuru Raj, J, Pethuru Raj Chelliah

Overview of this book

Enterprise Architecture (EA) is typically an aggregate of the business, application, data, and infrastructure architectures of any forward-looking enterprise. Due to constant changes and rising complexities in the business and technology landscapes, producing sophisticated architectures is on the rise. Architectural patterns are gaining a lot of attention these days. The book is divided in three modules. You'll learn about the patterns associated with object-oriented, component-based, client-server, and cloud architectures. The second module covers Enterprise Application Integration (EAI) patterns and how they are architected using various tools and patterns. You will come across patterns for Service-Oriented Architecture (SOA), Event-Driven Architecture (EDA), Resource-Oriented Architecture (ROA), big data analytics architecture, and Microservices Architecture (MSA). The final module talks about advanced topics such as Docker containers, high performance, and reliable application architectures. The key takeaways include understanding what architectures are, why they're used, and how and where architecture, design, and integration patterns are being leveraged to build better and bigger systems.
Table of Contents (13 chapters)
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Summary

Although the development field of data analytics is not new, it has become more critical than ever as it experiences prodigious quantities of data generated by businesses, sensors, applications, and so on. Once the generated data gets stored, it can give extraordinary insights and helps not only business enterprises but also government and non-government enterprises, social communities, the economy, and much more.

In current technology trends, big data has been involved in many evolutions, from just buzzwords to crunching data from machine learning algorithms. With the exponential explosion of high velocity, high volume, high variety, and the veracity of data sources and streams (the four V's), big data has become the inevitable representative of the architectures, tools, and technologies that handle enterprises increasingly demanding requirements.

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