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Cloud Scale Analytics with Azure Data Services

Cloud Scale Analytics with Azure Data Services

By : Borosch
4.9 (7)
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Cloud Scale Analytics with Azure Data Services

Cloud Scale Analytics with Azure Data Services

4.9 (7)
By: Borosch

Overview of this book

Azure Data Lake, the modern data warehouse architecture, and related data services on Azure enable organizations to build their own customized analytical platform to fit any analytical requirements in terms of volume, speed, and quality. This book is your guide to learning all the features and capabilities of Azure data services for storing, processing, and analyzing data (structured, unstructured, and semi-structured) of any size. You will explore key techniques for ingesting and storing data and perform batch, streaming, and interactive analytics. The book also shows you how to overcome various challenges and complexities relating to productivity and scaling. Next, you will be able to develop and run massive data workloads to perform different actions. Using a cloud-based big data-modern data warehouse-analytics setup, you will also be able to build secure, scalable data estates for enterprises. Finally, you will not only learn how to develop a data warehouse but also understand how to create enterprise-grade security and auditing big data programs. By the end of this Azure book, you will have learned how to develop a powerful and efficient analytical platform to meet enterprise needs.
Table of Contents (20 chapters)
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1
Section 1: Data Warehousing and Considerations Regarding Cloud Computing
4
Section 2: The Storage Layer
7
Section 3: Cloud-Scale Data Integration and Data Transformation
14
Section 4: Data Presentation, Dashboarding, and Distribution

Provisioning Databricks

Provisioning a Databricks workspace is as easy as the services in the previous chapters:

  1. First, navigate to the Azure portal and click Create a resource.
  2. In the search box, type Databricks and select Azure Databricks from the quick results displayed beneath the search. The Databricks info is displayed.
  3. Click Create and start the provisioning.
  4. In the Basics blade, fill in or select the values for the input fields. You will need to select the subscription to build your Azure Data Factory (ADF) and either select an existing resource group or create a new one. See Chapter 3, Understanding the Data Lake Storage Layer, for a description of resource groups. You want to name your workspace here and assign it to the most suitable region for you. As regards the Pricing Tier, please select the appropriate one. For a first test, you might select Trial (Premium - 14 Days Free DBUs) as this won't cost anything. You can then proceed with Next: Networking...
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