Book Image

Cloud Analytics with Microsoft Azure - Second Edition

By : Has Altaiar, Jack Lee, Michael Peña
Book Image

Cloud Analytics with Microsoft Azure - Second Edition

By: Has Altaiar, Jack Lee, Michael Peña

Overview of this book

Cloud Analytics with Microsoft Azure serves as a comprehensive guide for big data analysis and processing using a range of Microsoft Azure features. This book covers everything you need to build your own data warehouse and learn numerous techniques to gain useful insights by analyzing big data. The book begins by introducing you to the power of data with big data analytics, the Internet of Things (IoT), machine learning, artificial intelligence, and DataOps. You will learn about cloud-scale analytics and the services Microsoft Azure offers to empower businesses to discover insights. You will also be introduced to the new features and functionalities added to the modern data warehouse. Finally, you will look at two real-world business use cases to demonstrate high-level solutions using Microsoft Azure. The aim of these use cases will be to illustrate how real-time data can be analyzed in Azure to derive meaningful insights and make business decisions. You will learn to build an end-to-end analytics pipeline on the cloud with machine learning and deep learning concepts. By the end of this book, you will be proficient in analyzing large amounts of data with Azure and using it effectively to benefit your organization.
Table of Contents (7 chapters)

Machine learning on Azure

There are multiple ways to perform machine learning on Azure. Microsoft enables data science to be more accessible to all types of users and empowers data scientists to be more productive. Microsoft provides a suite of technologies for developers, database engineers, and data scientists to create machine learning algorithms. Whatever your level of proficiency and expertise in data science, there is a useful Microsoft service, tool, or framework that can accelerate your machine learning journey.

Figure 3.29 depicts a machine learning landscape within the Microsoft Azure ecosystem. You can use pre-trained models with Azure Cognitive Services and directly integrate them with your applications without the need to set up a data pipeline. You can use popular frameworks such as TensorFlow and Keras in Azure, whether that's by installing them on a virtual machine or using a machine learning workspace. You can choose different platforms such as Azure Machine...