Building Cloud Data Platforms Solutions
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Building Cloud Data Platforms Solutions

An End-to-End Guide for Designing, Implementing, and Managing Robust Data Solutions in the Cloud

About the Book

"Building Cloud Data Platforms Solutions: An End-to-End Guide for Designing, Implementing, and Managing Robust Data Solutions in the Cloud" is a comprehensive resource designed to cater to a diverse range of professionals and enthusiasts seeking to harness the power of cloud technologies to build effective data platforms. This book is relevant to individuals at various stages of their careers and with different levels of expertise in data architecture, cloud computing, and data management.

Data architects will find this book invaluable as it offers a deep dive into the intricacies of designing and implementing data solutions in the cloud. It covers a wide range of topics, including data ingestion, storage, processing, integration, governance, and analytics, providing essential guidance, best practices, and real-world examples to help architects make informed decisions and construct scalable, secure, and efficient cloud data platforms.

Data engineers involved in the implementation and maintenance of data platforms will benefit greatly from the practical insights and techniques provided in this book. It offers guidance on data processing frameworks, data integration strategies, and data quality management, enabling data engineers to build end-to-end data solutions that meet the needs of their organizations.

Cloud architects responsible for designing cloud infrastructure and services will find this book highly relevant to their roles. It delves into cloud-native data platforms, exploring topics such as selecting the appropriate cloud services, optimizing performance, ensuring security, and managing scalability. By understanding the architectural principles and best practices outlined in the book, cloud architects can effectively design data platforms that leverage the full potential of cloud resources.

Data scientists and analysts working with large datasets and seeking to derive meaningful insights will find this book to be a valuable resource. It covers aspects such as data storage, processing, and analytics, providing practical guidance on leveraging cloud resources for data exploration, modeling, and visualization tasks.

IT managers and decision-makers considering the adoption of cloud data platforms or the migration of existing data infrastructure to the cloud will benefit from the insights provided in this book. It addresses key considerations, challenges, and benefits of cloud data solutions, assisting in making informed decisions and maximizing the potential of cloud technologies.

Finally, students pursuing degrees or conducting research in the fields of data management, cloud computing, or data engineering will find this book to be an essential reference. It covers fundamental concepts, industry trends, and practical aspects of building cloud data platforms, providing a solid foundation for their academic and professional journeys.

About the Author


As a Data Architect, I have had the privilege of working in the field of data management and architecture for many years for Total energies, AXA GO, ICF (SNCF Habitat), EDF and credit Agricole. During this time, I have had the opportunity to work on a variety of projects, ranging from small-scale data integrations to large-scale enterprise data solutions.

My passion for data architecture began early in my career, when I was working as a software developer. I became fascinated by the way that data was organized and managed within the applications I was building. This led me to explore data architecture in more depth, and I soon realized that I had found my calling.

Over the years, I have gained experience in a wide range of technologies and methodologies, including relational and non-relational data structures, ETL/ELT processes, data warehousing, big data, cloud computing, and more. I have also worked extensively with various data modeling techniques, such as ER modeling, dimensional modeling, and data vault modeling.

My work as a Data Architect has allowed me to work with clients across various industries, including healthcare, finance, retail, and manufacturing. I have worked on projects ranging from data migration and integration to large-scale data warehousing and business intelligence solutions.

In addition to my work as a Data Architect, I am also a passionate educator and writer. I have conducted numerous training sessions and workshops on various data-related topics and have written several articles and whitepapers on data architecture and related fields.

Also, I’m an MVP for many times. It's a recognition program that Microsoft runs to acknowledge and reward community members who contribute to the technical community through their expertise and leadership.

You can flow me on these platforms:

- YouTube channel: @Anouarbenzahra

- Twitter: @Anouarbenzahra

- NuGet package: Anouar

- LinkedIn: @Anouarbenzahra

- GitHub: @Anouarbenzahra 

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