Imagine an online store wanting to analyze daily sales.
This entire workflow is orchestrated, monitored, and retried by ADF.
Data Factory adheres to enterprise security standards:
| Feature | Azure Data Factory | SSIS (On-Prem) | |---|---|---| | Execution | Serverless (pay per run) | Requires dedicated server | | Scale | Auto-scales thousands of activities | Manual scale (more workers) | | Maintenance | Microsoft handles patches | DBA team required | | Hybrid Access | Self-Hosted IR | Gateway or VPN | | Cost Model | Consumption (DIU hours, pipeline activity) | Licensing + infrastructure | | Learning Curve | Low (UI based) | High (complex components) | javatpoint azure data factory
Lift & Shift Strategy: Use Azure-SSIS Integration Runtime. You can redeploy existing SSIS packages (.dtsx) into ADF without rewriting.
Error Handling:
Monitoring & Alerts:
Cost Management:
Git Integration:
Problem: Copy only new/updated rows from a source SQL table to a data lake. Solution: Imagine an online store wanting to analyze daily sales
If you are studying for certifications like DP-203 (Data Engineering on Microsoft Azure) or DP-900 (Azure Data Fundamentals), focus on:
Hands-on Labs (GitHub): Microsoft provides azure-data-factory-samples repository.
Javatpoint.com: Offers structured tutorials under "Azure Data Factory," neatly categorized into: This entire workflow is orchestrated, monitored, and retried