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Understanding Azure Data Factory = O...
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SpringerLink (Online service)
Understanding Azure Data Factory = Operationalizing Big Data and Advanced Analytics Solutions /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Understanding Azure Data Factory/ by Sudhir Rawat, Abhishek Narain.
Reminder of title:
Operationalizing Big Data and Advanced Analytics Solutions /
Author:
Rawat, Sudhir.
other author:
Narain, Abhishek.
Description:
XI, 368 p. 376 illus.online resource. :
Contained By:
Springer Nature eBook
Subject:
Application software. -
Online resource:
https://doi.org/10.1007/978-1-4842-4122-6
ISBN:
9781484241226
Understanding Azure Data Factory = Operationalizing Big Data and Advanced Analytics Solutions /
Rawat, Sudhir.
Understanding Azure Data Factory
Operationalizing Big Data and Advanced Analytics Solutions /[electronic resource] :by Sudhir Rawat, Abhishek Narain. - 1st ed. 2019. - XI, 368 p. 376 illus.online resource.
Chapter 1: Introduction to Data Analytics -- Chapter 2: Introduction to Azure Data Factory -- Chapter 3: Data Movement -- Chapter 4: Data Transformation-I -- Chapter 5: Data Transformation-II -- Chapter 6: Monitoring -- Chapter 7: Security -- Chapter 8: Executing SSIS Packages.
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 cloud Build and operationalize an ADF pipeline Modernize a data warehouse Be aware of performance and security considerations while moving data .
ISBN: 9781484241226
Standard No.: 10.1007/978-1-4842-4122-6doiSubjects--Topical Terms:
528147
Application software.
LC Class. No.: QA76.76.M52
Dewey Class. No.: 004.165
Understanding Azure Data Factory = Operationalizing Big Data and Advanced Analytics Solutions /
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Chapter 1: Introduction to Data Analytics -- Chapter 2: Introduction to Azure Data Factory -- Chapter 3: Data Movement -- Chapter 4: Data Transformation-I -- Chapter 5: Data Transformation-II -- Chapter 6: Monitoring -- Chapter 7: Security -- Chapter 8: Executing SSIS Packages.
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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 cloud Build and operationalize an ADF pipeline Modernize a data warehouse Be aware of performance and security considerations while moving data .
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