Book Image

Architectural Patterns

By : Anupama Murali, Harihara Subramanian J, Pethuru Raj Chelliah
Book Image

Architectural Patterns

By: Anupama Murali, Harihara Subramanian 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)

Big data analysis and technology concepts

Let's start with the technology prerequisites for big data analysis, and then we will cover the life cycle of big data analysis. The prerequisites are:

  • Flexible architectures, that supports various data types and patterns
  • Upstream use of analytics for data relevance optimization
  • Advanced analytics and real-time visualization to accelerate actions and understandings
  • Collaborative approaches for aligning stakeholders

Data analysis life cycle

Big data analysis life cycle provides a step-by-step methodology for organizing the data activities and tasks related to data acquiring, processing, analyzing and repurposing. The following are the stages of data analysis life cycle with a...