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

This chapter took you through the Azure Purview preview. You have seen how to connect to data sources and how to set up scans to parse not only your data sources but also your whole modern data warehouse.

You have learned how to use classification rules in your scan rule sets to classify your data. You have seen how to create your own custom classifications and add them to your scans.

In the second part of the chapter, you saw how Purview integrates with other services such as Azure Synapse Analytics, where Purview can help increase productivity by integrating with the Synapse search and the Synapse compute components, such as the serverless SQL engine, the Spark engine, and Synapse pipelines.

You have examined how to integrate Power BI to be able to scan Power BI datasets, reports, and dashboards and how to add this information to the Purview data lineage part.

Finally, you have seen how Purview integrates with Azure Data Factory and can display data lineage...