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

Examining Azure Machine Learning

Azure Machine Learning will offer you a wide collection of capabilities to develop, train, and deploy machine learning models. Additionally, the environment supports you with the automation and management of your models. This includes the versioning and tracking not only of the models but also the training data that you use to build and retrain them.

Browsing the different Azure ML tools

As mentioned, Azure Machine Learning comes with a collection of tools and functionalities to support you in any aspect of the machine learning life cycle:

  • Azure ML Designer: A graphical interface to build machine learning models on a point-and-click basis.
  • Jupyter Notebooks: A programming interface where you can build your own ML models using Python.
  • R Scripts/Notebooks: Programming interface where you can build your own ML models using R.
  • Many Models Solution Accelerator: Offers you capabilities to work with thousands of ML models if needed...