BPB Publication Hands-on Cloud Analytics with MS Azure Stack

Description

Data is the key input for Analytics. Building and implementing data platforms such as Data Lakes, modern Data Marts, and Analytics at scale require the right cloud platform that Azure provides through its services.

The book starts by sharing how analytics has evolved and continues to evolve. Following the introduction, you will deep dive into ingestion technologies. You will learn about Data processing services in Azure. You will next learn about what is meant by a Data Lake and understand how Azure Data Lake Storage is used for analytical workloads.

You will then learn about critical services that will provide actual Machine Learning capabilities in Azure. The book also talks about Azure Data Catalog for cataloging, Azure AD for Access Management, Web Apps and PowerApps for cloud web applications, Cognitive services for Speech, Vision, Search and Language, Azure VM for computing and Data Science VMs, Functions as serverless computing, Kubernetes and Containers as deployment options. Towards the end, the book discusses two use cases on Analytics.

Tagline

Explore and work with various Microsoft Azure services for real-time Data Analytics

Key Features

Understanding what Azure can do with your data

Understanding the analytics services offered by Azure

Understand how data can be transformed to generate more data

Understand what is done after a Machine Learning model is built

Go through some Data Analytics real-world use cases

What Will You Learn

Explore and work with various Azure services

Orchestrate and ingest data using Azure Data Factory

Learn how to use Azure Stream Analytics

Get to know more about Synapse Analytics and its features

Learn how to use Azure Analysis Services and its functionalities

Who This Book is For

This book is for anyone who has basic to intermediate knowledge of cloud and analytics concepts and wants to use Microsoft Azure for Data Analytics. This book will also benefit Data Scientists who want to use Azure for Machine Learning.