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

Discovering additional knowledge

The following is some advice that you might find useful.

Do:

  • Plan for security from day one: Where are your trade-offs between security and usability?
  • Enforce as much discipline as needed, but not more than is really necessary. Your data lake needs to serve your Data Scientists, as well as other communities in your company. Your modern data warehouse needs some agility.
  • Structure your zones clearly and stick to the plan. If you need to redesign, don't do so in your already started structure.
  • Implement a Data Catalog (we will talk about this in Chapter 14, Establishing Data Governance) to enable easy data discovery.
  • Integrate with DevOps for a controlled and repeatable system.

Don't:

  • Don't mix different formats. Always stick to one single file format per folder. You will often want to read all the files in a folder in one go.
  • Don't forget naming conventions!