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

Summary

In this chapter, you have learned about Power BI and the options to create and deliver datasets, reports, and dashboards to your consumers. You have seen how to publish reports with their datasets to the Power BI service, where you can share and collaborate on your analysis.

You have seen how to build DAX calculations and the options that you have for RLS implementation on your models.

We have also discussed the creation of visuals and how they interact with each other and the data model.

You have learned how to publish your reports to the Power BI service and how to create dashboards from reporting visuals. With the created dashboard, you have investigated Q&A and seen how to export data for further usage.

Furthermore, you have learned about AAS, Power BI, and Excel as the clients for the columnstore database.

Finally, you have read about Azure Data Share and the options for automating the exchange of data between Azure subscriptions.

In Chapter 13...