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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

Thinking about different sizes

When you look at your engineered requirements and go through all the Azure data services that can form a modern data warehouse, you still might find it complex to decide which services to pick. And with the generic reference architecture in mind, there is no silver bullet to provision so that everything is fine. But let's examine some considerations about sizes, performance, and cost. One of the beauties of the cloud in general, and the ADS framework on Azure in particular, is that you can always switch gears once you recognize your system is too small, you need far more punch for your calculations, or to ensure speed for your users. Don't get me wrong – some services can be cumbersome to replace. However, it is still far easier to replace something than to rebuild everything from scratch.

Let's check out the three different sizes of modern data warehouse by using S, M, and L as rough indicators of our requirements.

Planning...

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