Optimizing Data Pipelines with Azure Data Factory
summary
Claims concrete outcomes: Azure Data Factory orchestrates linked services, datasets, activities and pipelines with event triggers, retries and checkpoints and sends alerts to email or Teams. A case study shows an ETL pipeline dropping from 8 hours to 45 minutes (about 91% faster); slides quote 78% faster processing and 63% cost reduction. Advice includes reusable pipeline templates, organize by domain, check code into Git, enable Azure monitoring and leverage runtime integrations.
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chapters (7)
- 0:00Introduction and Session Overview
- 0:20Today's Data Challenges
- 1:19Introducing Azure Data Factory
- 2:01Azure Data Factory Components
- 3:16Benefits and Features of Azure Data Factory
- 5:29Case Study and Best Practices
- 6:49Conclusion and Final Thoughts
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