Building a PySpark Data Pipeline with Azure SQL Database and Synapse Analytics

Scenario:
In this tutorial, we will walk through the process of creating a PySpark data pipeline using Databricks, fetching data securely from Azure SQL Database, applying transformations, and storing the results in Azure Synapse Analytics (Azure SQL Data Warehouse).
We will cover advanced topics such as secure credential handling, data partitioning, Spark session isolation levels, and a basic transaction mechanism.
Data engineering often involves the extraction, transformation, and loading (ETL) of data across various platforms.
Throughout the tutorial, we'll address best practices, advanced configurations, and error handling for a robust and efficient data pipeline.
Github link: github.com/ekh...