Cloud Scale Analytics with Azure Data Services: Build modern data warehouses on Microsoft Azure
by: Patrik Borosch
Publisher finelybook 出版社: Packt Publishing (July 23,2021)
Language 语言: English
Print Length 页数: 520 pages
ISBN-10: 1800562934
ISBN-13: 9781800562936
Book Description
By finelybook
A practical guide to implementing a scalable and fast state-of-the-art analytical data estate
Key Features
Store and analyze data with enterprise-grade security and auditing
Perform batch,streaming,and interactive analytics to optimize your big data solutions with ease
Develop and run parallel data processing programs using real-world enterprise scenarios
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.
by: the end of this Azure book,you will have learned how to develop a powerful and efficient analytical platform to meet enterprise needs.
What you will learn
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
