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Cloud Scale Analytics with Azure Data Services

You're reading from Cloud Scale Analytics with Azure Data Services Build modern data warehouses on Microsoft Azure

Product type Paperback

Published in Jul 2021

Publisher Packt

ISBN-13 9781800562936

Length 520 pages

Edition 1st Edition

Tools

Azure

Concepts

Data Streaming

Author (1):

Patrik Borosch

View More author details

Table of Contents (20) Chapters

Preface

1. Section 1: Data Warehousing and Considerations Regarding Cloud Computing

2. Chapter 1: Balancing the Benefits of Data Lakes Over Data Warehouses FREE CHAPTER

3. Chapter 2: Connecting Requirements and Technology

4. Section 2: The Storage Layer

5. Chapter 3: Understanding the Data Lake Storage Layer

6. Chapter 4: Understanding Synapse SQL Pools and SQL Options

7. Section 3: Cloud-Scale Data Integration and Data Transformation

8. Chapter 5: Integrating Data into Your Modern Data Warehouse

9. Chapter 6: Using Synapse Spark Pools

10. Chapter 7: Using Databricks Spark Clusters

11. Chapter 8: Streaming Data into Your MDWH

12. Chapter 9: Integrating Azure Cognitive Services and Machine Learning

13. Chapter 10: Loading the Presentation Layer

14. Section 4: Data Presentation, Dashboarding, and Distribution

15. Chapter 11: Developing and Maintaining the Presentation Layer

16. Chapter 12: Distributing Data

17. Chapter 13: Introducing Industry Data Models

18. Chapter 14: Establishing Data Governance

19. Other Books You May Enjoy

Technical requirements

You will again provision Azure services and combine them. Therefore, you will need the following:

An Azure subscription where you have at least contributor rights, or you are the owner
The right to provision Azure Cognitive Services
The right to provision the Azure Machine Learning service
The right to register an app in Azure Active Directory
The right to provision the Azure Key Vault service
Your data lake from Chapter 3, Understanding the Data Lake Storage Layer
Your Synapse Analytics workspace from Chapter 4, Understanding Synapse SQL Pools and SQL Options, and Chapter 6, Using Synapse Spark Pools

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Authors (1)

Borosch

Borosch

Patrik Borosch is a cloud solution architect for data and AI at Microsoft Switzerland GmbH. He has more than 25 years of BI and analytics development, engineering, and architecture experience and is a Microsoft Certified Data Engineer and a Microsoft Certified AI Engineer. Patrik has worked on numerous significant international data warehouse, data integration, and big data projects. Through this, he has built and extended his experience in all facets, from requirements engineering to data modeling and ETL, all the way to reporting and dashboarding. At Microsoft Switzerland, he supports customers in their journey into the analytical world of the Azure Cloud.

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