Azure Synapse - Deployment - 1.5

Before deploying the Generated Artifacts, please:

You should now have the Notebook files inside Azure Synapse Analytics ready for deployment.

We will explain how to deploy the generated artifacts using the target environment Azure Synapse.

To deploy the generated Artifacts:

Open Azure Synapse Analytics with the Workspace web URL provided in the Azure Synapse Workspace resource:
Azure Synapse Analytics is opened:
Click on the Develop menu on the left-hand-side:
Open the 500_Deploy_and_Load_DataVault_Synapse.ipynb file, which contains three steps:
1. %run XXX_Deployment.ipynb: Deploy the code
2. %run XXX_SimpleLoadExecution.ipynb: Load the data
3. %run XXX_SelectResults.ipynb: Display the results
Select the Apache Spark Pool (bgaasspark33v2 in our example)
Execute step 1

The deployment is done:
- Open Azure Storage Explorer
- You should have new folders, one by layer, created in your Target folder inside the Target Storage Account:
- Each layer folder contains one folder per Target Model Object, for example for the stage layer:
- Each Target Model Object folder contains a folder delta_log with the needed files to be able to load the date later:

If you want to start a new deployment, please:

Clear the Target Data Lake folder (claire-data-lake in our example).
If you want to change the Target Data Lake folder, please:
- Replace the placeholders with the new folder
- Delete the existing databases because they are linked to the previous folder by executing the following code in a Notebook:

%%pyspark
spark.sql("DROP DATABASE IF EXISTS stage CASCADE")

%%pyspark
spark.sql("DROP DATABASE IF EXISTS rawvault CASCADE")

%%pyspark
spark.sql("DROP DATABASE IF EXISTS businessvault CASCADE")