Architecting Modern Data Platforms

This book provides practical guidance on building big data infrastructure on-premises and in the cloud, architecting a modern data platform, and overcoming challenges in Hadoop projects. It is ideal for enterprise architects, IT managers, application architects, and data engineers.

Format: Paperback / softback
Length: 640 pages
Publication date: 04 January 2019
Publisher: O'Reilly Media, Inc, USA

Big data technologies have gained significant attention in recent years, but integrating these technologies into an end-to-end enterprise data platform remains a challenging task that requires specialized knowledge. This practical book aims to bridge that gap by providing comprehensive guidance on building big data infrastructure both on-premises and in the cloud, as well as architecting a modern data platform that meets the needs of modern businesses.

Ideal for enterprise architects, IT managers, application architects, and data engineers, this book offers a comprehensive approach to overcoming the many challenges that arise during Hadoop projects. It begins by providing a thorough technical primer that explores the vast landscape of tools available in the Hadoop and big data realm. This primer covers infrastructure, platform, and taking Hadoop to the cloud, providing readers with a solid foundation for understanding these complex topics.

In the infrastructure section, the book delves into all component layers of a modern data platform, from the server to the data center. It emphasizes the importance of establishing a solid foundation for data in the enterprise, ensuring that data is accessible, secure, and reliable. Readers will learn about the various hardware and software components involved in building a big data infrastructure, as well as best practices for configuring and managing them.

The platform section covers aspects of deployment, operation, security, high availability, and disaster recovery. It explains how to integrate a big data platform with the rest of the enterprise IT infrastructure, ensuring seamless integration and compatibility with existing systems. Readers will learn about deployment strategies, such as bare metal, virtual machines, and cloud platforms, as well as how to optimize platform performance and scalability.

The taking Hadoop to the cloud section focuses on the important architectural aspects of running a big data platform in the cloud while maintaining enterprise security and high availability. It discusses strategies for architecting a cloud-based big data platform, such as using containerization and microservices, and provides guidance on implementing cloud security measures. Readers will also learn about cloud-based storage solutions, such as Amazon S3 and Google Cloud Storage, and how to integrate them with big data platforms.

Throughout the book, real-world examples and case studies are used to illustrate the concepts and techniques discussed. These examples help readers understand how big data technologies can be applied in various industries and business scenarios, and provide practical insights into the challenges and opportunities associated with building and managing a modern data platform.

In conclusion, this book is a valuable resource for anyone looking to build big data infrastructure and architect a modern data platform. It provides comprehensive coverage of the key topics involved in big data projects, including infrastructure, platform, and taking Hadoop to the cloud. With its practical approach and real-world examples, it is ideal for enterprise architects, IT managers, application architects, and data engineers who want to stay up-to-date with the latest trends and best practices in big data.

Weight: 1106g
Dimension: 181 x 234 x 33 (mm)
ISBN-13: 9781491969274