Understanding Azure Data Factory: Operationalizing Big Data and Advanced Analytics Solutions - Brossura

Rawat, Sudhir; Narain, Abhishek

Brossura

ISBN 10: 1484241215 ISBN 13: 9781484241219

Casa editrice: Apress, 2018

Riassunto

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 

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.

Su questo libro

Informazioni sull?autore

Sudhir Rawat is a senior software engineer at Microsoft Corporation. He has 15 years of experience in turning data to insights. He is involved in various activities, including development, consulting, troubleshooting, and speaking. He works extensively on the data platform. He has delivered sessions on platforms at Microsoft TechEd India, Microsoft Azure Conference, Great India Developer Summit, SQL Server Annual Summit, Reboot (MVP), and many more. His certifications include MCITP, MCTS, MCT on SQL Server Business Intelligence, MCPS on Implementing Microsoft Azure Infrastructure Solutions, and MS on Designing and Implementing Big Data Analytics Solutions.

Abhishek Narain works as a technical program manager on the Azure Data Governance team at Microsoft. Previously he has worked as a consultant at Microsoft and Infragistics and he has worked on various Azure services and Windows app development projects. He is a public speaker and regularly speaks at various events, including Node Day, Droidcon, Microsoft TechEd, PyCon, the Great India Developer Summit and many others. Before joining Microsoft, he was awarded the Microsoft MVP designation.

 

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 

Dettagli dell'edizione

• Editore: Apress
• Data di pubblicazione: 2018
• Lingua: Inglese
• ISBN 10: 1484241215
• ISBN 13: 9781484241219
• Rilegatura: Copertina flessibile
• Numero edizione: 1
• Numero di pagine: 380
• Contatto del produttore: non disponibile
• Persona responsabile: non disponibile