Azure Data and AI Architect Handbook - Baelen, Breght van

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Résumé :
Master core data architecture design concepts and Azure Data & AI services to gain a cloud data and AI architect's perspective to developing end-to-end solutions Purchase of the print or Kindle book includes a free PDF eBook Key Features: Translate and implement conceptual architectures with the right Azure services Inject artificial intelligence into data solutions for advanced analytics Leverage cloud computing and frameworks to drive data science workloads Book Description: With data's growing importance in businesses, the need for cloud data and AI architects has never been higher. The Azure Data and AI Architect Handbook is designed to assist any data professional or academic looking to advance their cloud data platform designing skills. This book will help you understand all the individual components of an end-to-end data architecture and how to piece them together into a scalable and robust solution. You'll begin by getting to grips with core data architecture design concepts and Azure Data & AI services, before exploring cloud landing zones and best practices for building up an enterprise-scale data platform from scratch. Next, you'll take a deep dive into various data domains such as data engineering, business intelligence, data science, and data governance. As you advance, you'll cover topics ranging from learning different methods of ingesting data into the cloud to designing the right data warehousing solution, managing large-scale data transformations, extracting valuable insights, and learning how to leverage cloud computing to drive advanced analytical workloads. Finally, you'll discover how to add data governance, compliance, and security to solutions. By the end of this book, you'll have gained the expertise needed to become a well-rounded Azure Data & AI architect. What You Will Learn: Design scalable and cost-effective cloud data platforms on Microsoft Azure Explore architectural design patterns with various use cases Determine the right data stores and data warehouse solutions Discover best practices for data orchestration and transformation Help end users to visualize data using interactive dashboarding Leverage OpenAI and custom ML models for advanced analytics Manage security, compliance, and governance for the data estate Who this book is for: This book is for anyone looking to elevate their skill set to the level of an architect. Data engineers, data scientists, business intelligence developers, and database administrators who want to learn how to design end-to-end data solutions and get a bird's-eye view of the entire data platform will find this book useful. Although not required, basic knowledge of databases and data engineering workloads is recommended.

Biographie:
Olivier Mertens is a cloud solution architect for Azure data and AI at Microsoft, based in Dublin, Ireland. In this role, he assisted organizations in designing their enterprise-scale data platforms and analytical workloads. Next to his role as an architect, Olivier leads the technical AI expertise for Microsoft EMEA in the corporate market. This includes leading knowledge sharing and internal upskilling, as well as solving highly complex or strategic customer AI cases. Before his time at Microsoft, he worked as a data scientist at a Microsoft partner in Belgium.Olivier is a lecturer for generative AI and AI solution architectures, a keynote speaker for AI, and holds a master's degree in information management, a postgraduate degree as an AI business architect, and a bachelor's degree in business management.

Sommaire:
Master core data architecture design concepts and Azure Data & AI services to gain a cloud data and AI architect's perspective to developing end-to-end solutions Purchase of the print or Kindle book includes a free PDF eBook Key Features: Translate and implement conceptual architectures with the right Azure services Inject artificial intelligence into data solutions for advanced analytics Leverage cloud computing and frameworks to drive data science workloads Book Description: With data's growing importance in businesses, the need for cloud data and AI architects has never been higher. The Azure Data and AI Architect Handbook is designed to assist any data professional or academic looking to advance their cloud data platform designing skills. This book will help you understand all the individual components of an end-to-end data architecture and how to piece them together into a scalable and robust solution. You'll begin by getting to grips with core data architecture design concepts and Azure Data & AI services, before exploring cloud landing zones and best practices for building up an enterprise-scale data platform from scratch. Next, you'll take a deep dive into various data domains such as data engineering, business intelligence, data science, and data governance. As you advance, you'll cover topics ranging from learning different methods of ingesting data into the cloud to designing the right data warehousing solution, managing large-scale data transformations, extracting valuable insights, and learning how to leverage cloud computing to drive advanced analytical workloads. Finally, you'll discover how to add data governance, compliance, and security to solutions. By the end of this book, you'll have gained the expertise needed to become a well-rounded Azure Data & AI architect. What You Will Learn: Design scalable and cost-effective cloud data platforms on Microsoft Azure Explore architectural design patterns with various use cases Determine the right data stores and data warehouse solutions Discover best practices for data orchestration and transformation Help end users to visualize data using interactive dashboarding Leverage OpenAI and custom ML models for advanced analytics Manage security, compliance, and governance for the data estate Who this book is for: This book is for anyone looking to elevate their skill set to the level of an architect. Data engineers, data scientists, business intelligence developers, and database administrators who want to learn how to design end-to-end data solutions and get a bird's-eye view of the entire data platform will find this book useful. Although not required, basic knowledge of databases and data engineering workloads is recommended....