Microsoft Fabric Training in Chennai - Microsoft Fabric Training.pptx

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1. Introduction to Microsoft Fabric Dataflow & Pipelines

2. What Are Dataflows? Dataflows prepare and clean data from multiple sources They use Power Query to define transformation logic Support both cloud and on-premises data connectors Enable reusable data models across workspaces Improve data consistency and quality

3. What Are Pipelines? Pipelines orchestrate data movement and transformation Enable scheduling and monitoring of data workflows Support complex data dependencies and tasks Integrate with Data Factory and Synapse Provide visual pipeline designer for ease of use

4. Building Your First Dataflow Open Microsoft Fabric workspace Navigate to ‘Dataflows Gen2’ section Connect to data sources (SQL, Azure, API, etc.) Apply transformation steps using Power Query Save and validate your dataflow structure

5. Creating a Pipeline in Microsoft Fabric Access the ‘Data Factory’ experience within Fabric Create a new pipeline from the workspace Add activities like Copy Data, Data Flow, and Notebooks Set parameters and define task dependencies Validate and publish your pipeline

6. Connecting Dataflows and Pipelines Use pipelines to trigger and run dataflows automatically Schedule executions based on business needs Monitor pipeline status through the Fabric dashboard Enable alerts for failed runs or delays Achieve seamless data refresh and automation

7. Monitoring and Managing Workflows Use the monitoring hub to track dataflow runs View performance metrics and data refresh duration Manage execution failures with error logs Reschedule or rerun failed tasks easily Ensure consistent data delivery across systems

8. Best Practices for Dataflows & Pipelines Use parameterization for flexible workflows Leverage reusable templates and data connections Document all transformation steps clearly Implement data validation at every stage Secure credentials and monitor access permissions

9. Conclusion & Next Steps Dataflows and pipelines streamline Fabric data automation They ensure clean, consistent, and reliable data movement Integrate AI and analytics seamlessly through Fabric tools Explore advanced orchestration and monitoring options Start building scalable data workflows today!

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