Best Azure Data Engineer Training | Best Data Engineer Course in Hyderabad

1. Introduction To ADF? Important Concepts in Azure Data Factory +91-9989971070 www.visualpath.in

2. Introduction to Azure Data Factory (ADF) • Azure Data Factory (ADF) is a cloud-based data integration service provided by Microsoft. It enables users to create, schedule, and orchestrate data pipelines that move and transform data from various sources to various destinations. • This makes ADF an essential tool for organizations looking to manage and manipulate data at scale. www.visualpath.in

3. Key Features of Azure Data Factory • Scalability: ADF can handle large volumes of data, making it suitable for enterprises of all sizes. • Flexibility: It supports a wide range of data sources and destinations, including on-premises and cloud-based systems. • Cost-Effective: With a pay-as-you-go pricing model, ADF allows organizations to manage costs effectively. www.visualpath.in

4. Important Concepts in Azure Data Factory • Pipelines • Pipelines are the core component of ADF. They are groups of activities that perform data movement and transformation tasks. Each pipeline can consist of multiple activities, allowing for complex workflows. • Activities • Activities define the actions that need to be performed within a pipeline. They can be data movement activities (such as copying data from one location to another) or data transformation activities (such as running a Spark job to process data). www.visualpath.in

5. Datasets • Datasets represent the data structures within ADF. They define the schema and format of the data to be consumed or produced by activities. Datasets can be created for various data sources like SQL databases, Azure Blob Storage, and more. • Linked Services • Linked Services are connections to external data sources. They store the connection information needed for ADF to access and interact with data. www.visualpath.in

6. Triggers • Triggers in ADF are used to start pipelines. They can be scheduled to run at specific times or be event-based, triggering pipelines in response to data changes or external events. • Integration Runtime (IR) • ADF supports three types of IR: Azure IR (cloud-based), Self-hosted IR (on-premises or in a virtual network), and SSIS IR (for running SQL Server Integration Services packages). www.visualpath.in

7. Mapping Data Flows • Mapping Data Flows provide a code-free way to design and execute data transformation logic. • They offer a visual interface for building complex transformations, making it easier for users to design data processing workflows without needing extensive coding knowledge. www.visualpath.in

8. Conclusion • By understanding its core concepts—pipelines, activities, datasets, linked services, triggers, integration runtimes, and mapping data flows—users can effectively manage and process their data. • ADF's scalability, flexibility, and cost-effectiveness make it an ideal solution for modern data engineering and analytics needs. www.visualpath.in

9. CONTACT For More Information About Best Azure Data Engineer Training Address:- Flat no: 205, 2nd Floor, Nilgiri Block, Aditya Enclave, Ameerpet, Hyderabad-16 Ph No : +91-9989971070 Visit : www.visualpath.in E-Mail : online@visualpath.in

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