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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

Summary

In this chapter, we talked about one of the main components of any modern data warehouse architecture: Data Lake Storage. You learned how to provision Data Lake Storage Gen2 on the Azure portal.

We discussed how to organize a data lake from different angles and examined the zones and folder structures that you will need to implement for efficient usage. We also learned how to implement a data model in Data Lake Storage.

After that, we looked at the administrative side of the Data Lake storage account and talked about monitoring, backups, access control, and networking.

The Data Lake Storage account is not the only component in your modern data warehouse Architecture that will hold data for analysis. Stay tuned for the next chapter, where we will shed some light on the relational database components that we can add to the architecture.

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