Data Lake Analytics: Building Big Data Applications

This is a comprehensive technical guide to designing, building, deploying, and efficiently managing big data applications using Azure Data Lake and complementary Azure technologies. Microsoft Business Intelligence experts Stacia Varga and Michael Luckevich share their immense practical experience in developing big data applications, illuminating key concepts and best practices through clear and concise examples. You'll discover proven solutions for maximizing scalability, performance, and value, and avoiding pitfalls faced by early Azure big data implementers. Learn how to: Use Azure Data Lake Store and its Hadoop file system to support far higher volumes of read and write operations, as you leverage the extensive Hadoop ecosystem Efficiently orchestrate analytic processing workflows with Azure Data Factory, manage data movement between repositories, and transform data to meet your analytic requirements Implement Azure Data Lake Analytics and the U-SQL language to perform data processing tasks at the heart of your analytics solution Support diverse analytics workloads, including queries, image processing, machine learning, and sentiment analysis Optimally combine Azure Data Lake services to augment on-premises analytics infrastructure, build cloud-only infrastructure, or combine them in hybrid solutions