Cloud Scale Analytics with Azure Data Services
eBook Details:
- Paperback: 520 pages
- Publisher: WOW! eBook (July 23, 2021)
- Language: English
- ISBN-10: 1800562934
- ISBN-13: 978-1800562936
eBook Description:
Cloud Scale Analytics with Azure Data Services: A practical guide to implementing a scalable and fast state-of-the-art analytical data estate
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.
- Implement data governance with Azure services
- Use integrated monitoring in the Azure Portal and integrate Azure Data Lake Storage into the Azure Monitor
- Explore the serverless feature for ad-hoc data discovery, logical data warehousing, and data wrangling
- Implement networking with Synapse Analytics and Spark pools
- Create and run Spark jobs with Databricks clusters
- Implement streaming using Azure Functions, a serverless runtime environment on Azure
- Explore the predefined ML services in Azure and use them in your app
By the end of this Cloud Scale Analytics with Azure Data Services book, you will have learned how to develop a powerful and efficient analytical platform to meet enterprise needs.
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