| Description |
1 online resource (xviii, 194 pages) |
| Note |
Includes index. |
| Summary |
Build scalable ETL data pipelines in the cloud using Azure Data Factory's Mapping Data Flows. Each chapter of this book addresses different aspects of an end-to-end data pipeline that includes repeatable design patterns based on best practices using ADF's code-free data transformation design tools. The book shows data engineers how to take raw business data at cloud scale and turn that data into business value by organizing and transforming the data for use in data science projects and analytics systems. The book begins with an introduction to Azure Data Factory followed by an introduction to its Mapping Data Flows feature set. Subsequent chapters show how to build your first pipeline and corresponding data flow, implement common design patterns, and operationalize your result. By the end of the book, you will be able to apply what you've learned to your complex data integration and ETL projects in Azure. These projects will enable cloud-scale big analytics and data loading and transformation best practices for data warehouses. What You Will Learn Build scalable ETL jobs in Azure without writing code Transform big data for data quality and data modeling requirements Understand the different aspects of Azure Data Factory ETL pipelines from datasets and Linked Services to Mapping Data Flows Apply best practices for designing and managing complex ETL data pipelines in Azure Data Factory Add cloud-based ETL patterns to your set of data engineering skills Build repeatable code-free ETL design patterns Who This Book Is For Data engineers who are new to building complex data transformation pipelines in the cloud with Azure; and data engineers who need ETL solutions that scale to match swiftly growing volumes of data. |
| Contents |
Part I Getting Started with Azure Data Factory and Mapping Data Flows -- ETL for the Cloud Data engineer -- Introduction to Azure Data Factory -- Introduction to Mapping Data Flows -- Part II Designing Scalable ETL Jobs with ADF Mapping Data Flows -- Build Your First Pipeline -- Common ETL pipeline practices in ADF with mapping data flows -- Slowly changing dimensions -- Data deduplication -- Mapping data flow advanced topics -- Part III Operationalize your ETL Data Pipelines -- Basics od CI/CD and pipeline scheduling -- Monitor, manage, and optimize. |
| Subject |
Windows Azure.
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Windows Azure |
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Data warehousing.
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Database management.
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Information storage and retrieval systems -- Data processing.
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Cloud computing.
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Entrepôts de données (Informatique) |
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Bases de données -- Gestion. |
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Systèmes d'information -- Informatique. |
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Infonuagique. |
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Cloud computing |
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Data warehousing |
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Database management |
| Other Form: |
Print version: 1484286111 9781484286111 (OCoLC)1330407001 |
| ISBN |
9781484286128 (electronic bk.) |
|
148428612X (electronic bk.) |
| Standard No. |
10.1007/978-1-4842-8612-8 doi |
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