Azure Data and AI Architect Handbook
Packt Publishing Limited (Verlag)
978-1-80323-486-1 (ISBN)
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 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 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 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.
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. Breght Van Baelen is a Microsoft employee based in Dublin, Ireland, and works as a cloud solution architect for the data and AI pillar in Azure. He provides guidance to organizations building large-scale analytical platforms and data solutions. In addition, Breght was chosen as an advanced cloud expert for Power BI and is responsible for providing technical expertise in Europe, the Middle East, and Africa. Before his time at Microsoft, he worked as a data consultant at Microsoft Gold Partners in Belgium. Breght led a team of eight data and AI consultants as a data science lead. Breght holds a master’s degree in computer science from KU Leuven, specializing in AI. He also holds a bachelor’s degree in computer science from the University of Hasselt.
Table of Contents
Introduction to Data Architectures
Preparing for Cloud Adoption
Ingesting Data into the Cloud
Transforming Data on Azure
Storing Data for Consumption
Data Warehousing
The Semantic Layer
Visualizing Data Using Power BI
Advanced Analytics Using AI
Enterprise-Level Data Governance and Compliance
Introduction to Data Security
| Erscheinungsdatum | 03.08.2023 |
|---|---|
| Verlagsort | Birmingham |
| Sprache | englisch |
| Maße | 191 x 235 mm |
| Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| ISBN-10 | 1-80323-486-5 / 1803234865 |
| ISBN-13 | 978-1-80323-486-1 / 9781803234861 |
| Zustand | Neuware |
| Haben Sie eine Frage zum Produkt? |
aus dem Bereich
