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README.md

DDL Extraction Scripts pre-requisites

  • Deploy the scripts in this repository (Data Extract Scripts folder) in the source database.
  • The managed identity of Azure SQL Data Warehouse Server or Synapse Workspace should be added as a user.
  • Following permissions must be given to the Managed Identity before running data extraction scripts
    • GRANT ADMINISTER DATABASE BULK OPERATIONS TO [Managed Service Identity];
    • GRANT ALTER ANY EXTERNAL DATA SOURCE TO [Managed Service Identity];
    • GRANT ALTER ANY EXTERNAL FILE FORMAT TO [Managed Service Identity];
  • User running these scripts needs all of these permissions
    • ALTER SCHEMA permission on the local schema that will contain the new table or membership in the db_ddladmin fixed database role.
    • CREATE TABLE permission or membership in the db_ddladmin fixed database role.
    • SELECT permission on any objects referenced in the select_criteria.

deploy_and_create_migration_scripts_from_source.ps1 -> Deploy as SQL Package

  • The PS1 script has a parameter, $CreateSQlProject. If you enable this parameter, then the extracted sql scripts are deployed as a dacpac file to Synapse Data Warehouse in Microsoft Fabric.
  • The additional parameters such as $skipViews, $skipSp, $skipfunctions, $skipothers allows you to control which objects can be built, deployed.
  • The PS script uses dotnet build and the following dependencies at this time should be installed
    • Install Azure Data Studio Insider build
    • Once installed, install SQL Database Projects extension 1.3.0. Sql Database Projects 1.3.0
    • Install dotnet SDK if not installed. You can check the installed SDK's. dotnet --list-sdks
    • Install SQL Package Insider build from DacFx repository.
  • Update other PS1 script parameters such as $systemDacpacLocation, $dotnet, $sqlPackageLocation and $connectionString.
  • With this, this script helps you to extract sql scripts, create SQL Server Database Project targeting Synapse Data Warehouse in Microsoft Fabric and deploy the data warehouse using SQL Package. Note: You can use Azure Data Studio to manage database project.