Azure Data and AI Architect Handbook (eBook)
284 Seiten
Packt Publishing (Verlag)
978-1-80323-073-3 (ISBN)
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.
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 solutionsPurchase of the print or Kindle book includes a free PDF eBookKey FeaturesTranslate and implement conceptual architectures with the right Azure servicesInject artificial intelligence into data solutions for advanced analyticsLeverage cloud computing and frameworks to drive data science workloadsBook DescriptionWith 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 learnDesign scalable and cost-effective cloud data platforms on Microsoft AzureExplore architectural design patterns with various use casesDetermine the right data stores and data warehouse solutionsDiscover best practices for data orchestration and transformationHelp end users to visualize data using interactive dashboardingLeverage OpenAI and custom ML models for advanced analyticsManage security, compliance, and governance for the data estateWho this book is forThis 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.]]>
| Erscheint lt. Verlag | 31.7.2023 |
|---|---|
| Sprache | englisch |
| Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| ISBN-10 | 1-80323-073-8 / 1803230738 |
| ISBN-13 | 978-1-80323-073-3 / 9781803230733 |
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