Day 25: Monitor and Automate Like a Pro! 📊 Go beyond the portal by using the Monitoring UI for deep visual insights and Python/.NET SDKs to programmatically manage, trigger, and track your pipelines at scale. 🤖📈
#dataengineering #CloudComputing #DataAnalytics #microsoftazure https://t.co/AkIWUL4Oo1
#dataengineering #CloudComputing #DataAnalytics #microsoftazure https://t.co/AkIWUL4Oo1
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Day 24: Run Anything with Custom Activities! 💻 When built-in activities aren't enough, use Custom Activities powered by Azure Batch to run your own scripts (Python, PowerShell, C#) on a scalable, managed compute cluster. 🛠️☁️
#DataEngineering #cloudcomputing #DataScience https://t.co/OWtX0AavEt
#DataEngineering #cloudcomputing #DataScience https://t.co/OWtX0AavEt
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Day 23: Power Up with Databricks! 🧱 Scale your data processing by using the Databricks Notebook activity to run complex Spark jobs, Python, or SQL directly from your ADF pipelines. 🚀🔥
#DataEngineering #dataengineer #Microsoft365 #CloudComputing #databricks #DataDriven https://t.co/cQ6mA8J9KR
#DataEngineering #dataengineer #Microsoft365 #CloudComputing #databricks #DataDriven https://t.co/cQ6mA8J9KR
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Day 22: Automate Your Deployments! 🚀 Transition from manual changes to professional workflows by integrating Azure DevOps or GitHub, enabling version control, automated testing, and seamless code promotion across environments. 🛠️🔄
#DataEngineering #devops #dataanalytics https://t.co/p9P3RyqJGA
#DataEngineering #devops #dataanalytics https://t.co/p9P3RyqJGA
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Day 21: Keep Your Secrets Secret! 🔐 Secure your data pipelines by integrating Azure Key Vault to manage connection strings and passwords, ensuring that sensitive credentials never appear in plain text. 🛡️✨
#AzureDataFactory #dataengineering #DataAnalytics #DataScience https://t.co/bEEz8wmFFy
#AzureDataFactory #dataengineering #DataAnalytics #DataScience https://t.co/bEEz8wmFFy
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Day 20: Build Faster & Fail Smarter! 🛡️ Master pipeline resilience using Success/Failure constraints to handle errors gracefully, and boost performance by running activities in Parallel using the For-Each loop.
⚡📉
#dataengineering #datanalytics #machinelearning @Azure https://t.co/JcQG2h4ND5
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#dataengineering #datanalytics #machinelearning @Azure https://t.co/JcQG2h4ND5
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Day 17: Transform Without the Code! 🛠️ Master Mapping Data Flows to build complex, scalable data transformations visually—allowing you to join, filter, and aggregate data at scale without writing a single line of Spark code. 📊✨ #AzureDataFactory #DataEngineering #CloudComputing https://t.co/07VHt1xhrD
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Day 14: Lock It Down! 🔐 Stop hardcoding secrets and start using Managed Identities for password-less auth and Azure Key Vault as your secure digital safe. Security isn't just a feature—it's the foundation of a pro data pipeline! 🛡️☁️
#DataEngineering #CloudComputing #Database https://t.co/ftwmke7Cqr
#DataEngineering #CloudComputing #Database https://t.co/ftwmke7Cqr
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Day 13: Look Under the Hood! 🕵️♂️ Scale your observability by piping ADF Logs into Azure Monitor—unlocking long-term data retention, custom KQL insights, and proactive alerts before issues even arise. 📊🚀
#AzureDataFactory #dataengineering #DataProtection #DataPrivacy https://t.co/cwnfcyVWbW
#AzureDataFactory #dataengineering #DataProtection #DataPrivacy https://t.co/cwnfcyVWbW
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Day 12: Stay in Control! 🔍 Every great data engineer needs an eye on the engine. Master Debugging to catch errors before they hit production and Monitoring to track your pipeline's heartbeat in real-time. 📈🛠️
#AzureDataFactory #DataEngineering #CloudComputing #DataDriven https://t.co/oYGJXnhBH8
#AzureDataFactory #DataEngineering #CloudComputing #DataDriven https://t.co/oYGJXnhBH8
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Day 11: Transform like a Pro! 🔄 Use Mapping Data Flows for scalable, production-grade ETL, or Wrangling Data Flows (Power Query style) for quick, interactive data prep. Choose your tool and let Spark do the heavy lifting! ⚡️
#AzureDataFactory #DataEngineering #CloudComputing https://t.co/CGvxqKFrPE
#AzureDataFactory #DataEngineering #CloudComputing https://t.co/CGvxqKFrPE
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Day 7: Cloud or On-Prem? ☁️ The Integration Runtime (IR) is your pipeline's engine—choose Azure IR for seamless cloud-to-cloud power, or Self-Hosted IR to build a secure bridge to your private on-premises data!
#AzureDataFactory #DataEngineering #cloudcomputing #DataScience https://t.co/iHU0dh22B0
#AzureDataFactory #DataEngineering #cloudcomputing #DataScience https://t.co/iHU0dh22B0
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9.1K
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