Hands-on Cloud Analytics with Microsoft Azure Stack: Transform Your Data to Derive Powerful Insights Using Microsoft Azure

Description

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 builtGo through some Data Analytics real-world use casesDescription 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.What will you learnExplore and work with various Azure servicesOrchestrate and ingest data using Azure Data FactoryLearn how to use Azure Stream AnalyticsGet to know more about Synapse Analytics and its featuresLearn how to use Azure Analysis Services and its functionalitiesWho this book is forThis 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.Table of Contents 1. Data and its power 2. Evolution of Analytics and its Types 3. Internet of Things 4. AI and ML 5. Why cloud 6. What are a data lake and a modern datamart 7. Introduction to Azure services 8. Types of data 9. Azure Data Factory 10. Stream Analytics 11. Azure Data Lake Store and Azure Storage 12. Cosmos DB 13. Synapse Analytics 14. Azure Databricks 15. Azure Analysis Services 16. Power BI 17. Azure Machine Learning 18. Sample Architectures and synergies - Real-Time and Batch 19. Azure Data Catalog 20. Azure Active Directory 21. Azure Webapps 22. Power apps 23. Time Series Insights 24. Azure Cognitive Services 25. Azure Logicapps 26. Azure VM 27. Azure Functions 28. Azure Containers 29. Azure Kubernetes Service 30. Use Case 1 31. Use Case 2 About the Authors Prashila Naik has over 16 years of experience in the tech sector. She has worked for multiple global organizations, primarily in the data and analytics space. She has seen data and analytics grow from strength to strength and thinks it will always be one of the most interesting areas in technology ever. She She is also a writer who primarily writes creative fiction and non-fiction, as well as an occasional translator. Her short stories have been published in various leading literary journals in India and elsewhere.Your LinkedIn Profile: https://www.linkedin.com/in/prashila-naik-7645604