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

Chapter 8: Streaming Data into Your MDWH

More and more analytical projects need to show real-time or near real-time data, that is, data that is coming from online systems such as shops and trading platforms or IoT telemetry. You want to collect and analyze that data maybe even right as it hits your system. IoT data might give you input about the status and potential failure of machines on your shop floor, or you may just seek to display online data of your production. Shop telemetry could inform you about potential customer churn, or trading events might be checked for fraudulent behavior. There are multiple use cases as well as options to implement them on the Microsoft Azure platform.

This chapter will inform you about Azure Stream Analytics (ASA) and the configuration-based approach that this service offers. ASA is a fully managed PaaS component. You will learn how to set up the service and how to connect to sources and targets. You will learn about SQL queries with windowing...