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

Implementing workload management

You have read about control nodes and compute nodes in the preceding sections, and you will learn that you can add more compute nodes when your workload needs more power in the Scaling the database section. But keep in mind that adding compute nodes will also add cost to your bill at the end of the month.

Tip

Try and identify time slots where your database is not "hammered on" big time and either scale the database back down or, when you can afford to, hibernate it. You can save a lot of money by doing so. Development and testing environments are also good candidates for switching the database off when they aren't needed.

Fortunately, the Synapse product group has added some options to the database that will help you with optimizing the usage of a given compute environment before you need to scale the database. Workload management will enable you to set different priorities (workload importance) for different processes, to isolate...