Operationalizing Multi-Cloud Environments: Technologies, Tools and Use Cases, Nagarajan Rajganesh, Raj Pethuru, Thirunavukarasu Ramkumar
Автор: Gift Noah, Deza Alfredo Название: Practical Mlops: Operationalizing Machine Learning Models ISBN: 1098103017 ISBN-13(EAN): 9781098103019 Издательство: Wiley Рейтинг: Цена: 51000.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: MLOps offers a set of proven principles aimed at solving this problem in a reliable and automated way. This insightful guide takes you through what MLOps is (and how it differs from DevOps) and shows you how to put it into practice to operationalize your machine learning models.
Автор: Rawat Sudhir, Narain Abhishek Название: Understanding Azure Data Factory: Operationalizing Big Data and Advanced Analytics Solutions ISBN: 1484241215 ISBN-13(EAN): 9781484241219 Издательство: Springer Рейтинг: Цена: 55890.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Improve your analytics and data platform to solve major challenges, including operationalizing big data and advanced analytics workloads on Azure. You will learn how to monitor complex pipelines, set alerts, and extend your organization's custom monitoring requirements.
This book starts with an overview of the Azure Data Factory as a hybrid ETL/ELT orchestration service on Azure. The book then dives into data movement and the connectivity capability of Azure Data Factory. You will learn about the support for hybrid data integration from disparate sources such as on-premise, cloud, or from SaaS applications. Detailed guidance is provided on how to transform data and on control flow. Demonstration of operationalizing the pipelines and ETL with SSIS is included. You will know how to leverage Azure Data Factory to run existing SSIS packages. As you advance through the book, you will wrap up by learning how to create a single pane for end-to-end monitoring, which is a key skill in building advanced analytics and big data pipelines.
What You'll Learn
Understand data integration on Azure cloudBuild and operationalize an ADF pipelineModernize a data warehouseBe aware of performance and security considerations while moving data
Who This Book Is For
Data engineers and big data developers. ETL (extract, transform, load) developers also will find the book useful in demonstrating various operations.
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