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

Monitoring your streaming solution

As seen in Figure 8.9, you can see some information already on the Overview page of your ASA job. If you navigate to the Monitoring section of your ASA job, you can get further insights into your job.

In the Logs section, for example, you are presented with a list of predefined queries that will produce insights into all kinds of errors that can occur when you are running your ASA job:

Figure 8.16 – Available error queries in the Logs section

If you proceed to Metrics, you are taken to a chart editor where you can select from the available ASA metrics:

Figure 8.17 – ASA metrics view

You have metrics such as backlogged input events, data conversion errors, early input events, and failed function requests. This section will give you a deep insight into your ASA job.

If you want to set up alerts for your ASA job, such as the SU percentage utilization, for example (remember the Understanding...