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

Building data marts with Power BI

In our modern data warehouse architecture in Chapter 2, Connecting Requirements and Technology, you were introduced to Power BI as the central reporting tool if you are either planning for small-sized implementations or planning for an enterprise-wide analytical data estate.

Power BI offers a toolset to do the following:

  • Get data and wrangle it into the Power BI data model if required.
  • Store your data in a columnstore database for fast visualizing and reporting.
  • Equip you with a data analysis language called Data Analysis Expressions (DAX) to implement the business logic that you need for your reports and dashboards.
  • Develop all the required artifacts.
  • Publish datasets, reports, and dashboards and collaborate with your co-workers.

Understanding the Power BI ecosystem

If you examine the Power BI ecosystem, you will find different components that will serve the functions mentioned:

  • Power BI Desktop: This...