Azure Data Factory: Microsoft Data Integration Service

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Azure Data Factory is a cloud data integration service offered by Microsoft and designed to handle the complexities of transferring and transforming large volumes of data.

In a world where the diversity of data sources is increasingly greater, a tool capable of unifying, transforming and moving data is essential.

In this sense, Azure Data Factory stands out rcs data belarus a robust and flexible solution for professionals dealing with data engineering challenges, allowing the creation of automated workflows that integrate different platforms, whether on-premises, in the cloud or in hybrid environments.

In this article, I will explain some of the benefits of working with the tool, based on my experience leading a data team that has already implemented more than 40 business intelligence projects for companies such as Klabin, Sicoob and Crocs.



Summary
What is Azure Data Factory?
Why Azure Data Factory?
Azure Data Factory Structure and Components
1. Pipelines
2. Activities
3. Data Sets and Linked Services
4. Integration Runtime (IR)
Implementing Pipelines in Azure Data Factory
1. Defining the Pipeline Scope
2. Linked Services Configuration
3. Defining Data Sets
4. Creating Activities
5. Integration Runtime Configuration
6. Monitoring and Logs
Common Azure Data Factory Use Cases
Data Integration from Different Systems
Data Migration to the Cloud
Data Loading for Data Warehouses
Benefits of Azure Data Factory
Scalability
Integration with Other Tools
Hybrid Environment Support
Intuitive Visual Interface
Limitations and Considerations
Conclusion
What is Azure Data Factory?
Azure Data Factory is a cloud-based data integration solution offered by Microsoft . It allows you to move, transform, and integrate data from multiple sources, whether on-premises, in the cloud, or hybrid.

This service enables the construction of automated data pipelines that help organizations deal with large volumes of information, connecting heterogeneous systems and facilitating the analysis and use of data in a centralized manner.