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

Finding the right Azure tool for the right purpose

Now that we have a more detailed generic picture of the components that make a modern data warehouse, let's examine the available Azure services. We will try to identify the ones that are suitable for your requirements. All the following services are classified as Platform-as-a-Service (PaaS) components. And, as a consultant will always tell you, it depends.

While going through your engineered requirements, you should have a picture in mind of where you want to go. You will know about the data volume, data formats and sources, your transformations, the presentation strategy, and all the questions from the first section of this chapter (see Asking in the right direction).

The answers to the questions about volume, for example, together with data formats, will play a vital role in you selecting your storage component. They will point you to the DBs service that you will choose to implement your presentation layer in. There...