Book Image

Cloud Scale Analytics with Azure Data Services

By : Patrik Borosch
Book Image

Cloud Scale Analytics with Azure Data Services

By: Patrik 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)
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

Understanding Industry Data Models

Industry data models have been developed by different companies for a long time. Microsoft started to offer this approach with the Common Data Model (CDM), which spans all three cloud pillars of Microsoft (Azure, Office 365, and Dynamics 365). The goal is to easily interconnect data services with each other and follow a predefined structure that is known by all the components involved. If, for example, sales data is read from Dynamics 365, its structure is defined and already available for Data Factory. It can be written to Azure Data Lake Storage or Synapse SQL pools, and from there Power BI already knows the structure and can offer reports and dashboards.

The CDM can be adjusted to your needs. This means you, as the developer, can add attributes to existing entities, create additional entities, or skip the ones you don't need.

To learn more about industry data models, check out Chapter 13, Introducing Industry Data Models.

Note

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