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Cloud Analytics with Microsoft Azure: Build modern data warehouses with the combined power of analytics and Azure

Corsi di lingua
Inglese
Formato
Categoria

Non-fiction

Leverage the power of Azure to get efficient data insights from your big data in real time

Key Features • Explore the basics of cloud analytics using Azure

• Discover different ways to process and visualize your data easily

• Learn to use Azure Synapse Analytics (formerly known as Azure SQL Data Warehouse) to derive real-time customer insights

Book Description

With data being generated at an exponential speed, organizations all over the world are migrating their infrastructure to the cloud. Application management becomes much easier when you use a cloud platform to build, manage, and deploy your services and applications.

Cloud Analytics with Microsoft Azure covers all that you need to extract useful insights from your data. You'll explore the power of data with big data analytics, the Internet of Things (IoT), machine learning, artificial intelligence, and DataOps. You’ll also delve into data analytics by studying use cases that focus on creating actionable insights from near-real-time data. As you advance, you’ll 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'll have developed a solid understanding of data analytics with Azure and its practical implementation.

What you will learn • Explore the concepts of modern data warehouses and data pipelines

• Discover different design considerations while applying a cloud analytics solution

• Design an end-to-end analytics pipeline on the cloud

• Differentiate between structured, semi-structured, and unstructured data

• Choose a cloud-based service for your data analytics solutions

• Use Azure services to ingest, store and analyze data of any scale

Who this book is for

If you’re planning to adopt the cloud analytics model for your business, this book will help you understand the design and business considerations that you must keep in mind. Though not necessary, a basic understanding of data analytics concepts such as data streaming, data types, the machine learning life cycle, and Docker containers will help you get the most out of the book.

Has Altaiar is a software engineer at heart and a consultant by trade. Has lives in Melbourne, Australia, and is the Executive Director at vNEXT Solutions. His work focuses on data, IoT, and AI on Microsoft Azure, and two of his latest IoT projects won multiple awards. Has is also a Microsoft Azure MVP and a regular organizer and speaker at local and international conferences, including Microsoft Ignite, NDC, and ServerlessDays. He’s also a board member of the Global AI Community. You can follow him on Twitter at @hasaltaiar. Jack Lee is a senior Azure certified consultant and an Azure practice lead with a passion for software development, cloud, and DevOps innovations. He is an active Microsoft tech community contributor and has presented at various user groups and conferences, including the Global Azure Bootcamp at Microsoft Canada. Jack is an experienced mentor and judge at Hackathons and is also the president of a user group that focuses on Azure, DevOps, and software development. He has been recognized as a Microsoft MVP for his contributions to the tech community. You can follow Jack on Twitter at @jlee_consulting. Michael Peña is an experienced technical consultant based in Sydney, Australia. He is a Microsoft MVP and a certified professional with over 10 years of experience in data, mobile, cloud, web, and DevOps. Throughout these years, he wore various hats but considered himself a developer at heart. He is also an international speaker, having spoken at numerous events, including the Microsoft Ignite, NDC, DDD, Cross-Platform Summit, and various in-person and virtual meet-ups. Michael has interned with Microsoft and is also a Microsoft student partner alumnus. You can follow him on Twitter at @mjtpena.

© 2019 Packt Publishing (Ebook): 9781839214646

Data di uscita

Ebook: 26 novembre 2019

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