Can’t Load Data into Azure SQL? Fix It with Azure Data Factory Sink Transformations! 🚀
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Can’t Load Data into Azure SQL? Fix It with Azure Data Factory Sink Transformations! 🚀
6 651 просмотр · 3 г. назад
Pragmatic Works
342 тыс. подписчиков
6 651 просмотр · 3 г. назад
In this episode of the Azure Data Factory Data Flows Series, Austin Libal walks through how to create and configure a Sink Transformation inside Azure Data Factory to load transformed data into an Azure SQL Database. 🚀
Learn how to take data from a Data Lake, apply transformations using Mapping Data Flows, and successfully send the cleaned data into Azure SQL for reporting, analytics, and business intelligence workflows. 📊⚡
This tutorial covers:
✅ Creating a Sink Transformation in Azure Data Factory
✅ Connecting to Azure SQL Database
✅ Creating datasets and linked services
✅ Running Data Flows through Pipelines
✅ Debugging and monitoring pipeline executions
✅ Loading transformed movie rating data into SQL tables
Perfect for beginners learning:
🔹 Azure Data Factory
🔹 Azure SQL Database
🔹 ETL & ELT Processes
🔹 Mapping Data Flows
🔹 Azure Data Engineering
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⏱️ Video Timestamps
00:00 Introduction to Azure Data Factory Sink Transformation
00:55 Overview of Transforming Data from Data Lake to Azure SQL
01:29 Reviewing Movie Data Transformations
01:58 Opening Azure Data Factory Data Flow
02:31 Filtering and Sorting Data in Data Flows
03:08 Adding the Sink Transformation
03:48 Creating a New Azure SQL Dataset
04:17 Configuring Azure SQL Database Connection
04:49 Creating the Movie Ratings Table
05:21 Sink Transformation Settings Explained
05:58 Upserts, Truncate & Table Options
06:31 Creating a Pipeline in Azure Data Factory
07:05 Adding Data Flow Activity to Pipeline
07:38 Selecting the Data Flow for Execution
08:11 Running the Pipeline with Debug
08:46 Monitoring Pipeline Output & Rows Written
09:19 Verifying Data in Azure SQL Database
09:52 Reviewing Final Transformed Movie Data
10:30 Final Thoughts on Azure Data Factory Data Flows
11:02 Outro
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