{"id":28824,"date":"2019-11-07T09:00:08","date_gmt":"2019-11-07T17:00:08","guid":{"rendered":""},"modified":"2019-11-05T09:28:25","modified_gmt":"2019-11-05T17:28:25","slug":"new-in-azure-synapse-analytics-cicd-for-sql-analytics-using-sql-server-data-tools","status":"publish","type":"post","link":"https:\/\/www.microsoft.com\/en-us\/sql-server\/blog\/2019\/11\/07\/new-in-azure-synapse-analytics-cicd-for-sql-analytics-using-sql-server-data-tools\/","title":{"rendered":"New in Azure Synapse Analytics: CICD for SQL Analytics using SQL Server Data Tools"},"content":{"rendered":"

At Microsoft Ignite 2019,\u00a0we\u00a0announced<\/a>\u00a0Azure Synapse Analytics<\/strong>,\u00a0a major evolution of Azure SQL Data Warehouse.\u00a0The\u00a0same industry leading data warehouse<\/a>\u00a0now provides a whole new level of performance, scale, and analytics capabilities.\u00a0One of these capabilities is SQL Analytics, which provides a rich set of enterprise data warehousing features.<\/p>\n

Today we are announcing the general availability of the highest requested\u00a0feature<\/a> for SQL Analytics in Azure Synapse, SQL Server Data Tools (SSDT) database projects. This release includes support for SQL Server Data Tools with Visual Studio 2019 along with native platform integration with Azure DevOps providing built-in continuous integration and deployment (CI\/CD) capabilities for enterprise level deployments. This announcement also comes with support for the Schema Compare extension in Azure Data Studio for SQL Analytics.\u00a0\u00a0You can now expect a frictionless development and deployment experience on any platform for your analytics solution.<\/p>\n

\"Flow<\/p>\n

Since announcing preview support for SQL Server Data Tools (SSDT), customers have been able to use popular SQL Server Data Tools features such as Schema Compare, build, and publish for local development of their data warehouse.\u00a0Although\u00a0this has\u00a0helped\u00a0customers\u00a0accelerate\u00a0project\u00a0development, an automated build, test, and deployment infrastructure is\u00a0still critical for continuous integration and deployment (CI\/CD) scenarios.\u00a0Without the\u00a0native\u00a0integration with Azure DevOps, customers were\u00a0still\u00a0forced to\u00a0manually\u00a0write\u00a0PowerShell and TSQL scripts\u00a0integrated with Azure DevOps for an automated release process.<\/p>\n

With SQL Server Data Tools\u00a0generally available and native Azure DevOps support,\u00a0you can\u00a0now\u00a0set up stable release pipelines\u00a0without any custom code, and\u00a0changes to your data warehouse model\u00a0can be\u00a0safely\u00a0and automatically\u00a0promoted across development, testing, and production environments.\u00a0Preview customers\u00a0such as\u00a0T-Mobile\u00a0will now be\u00a0able to accelerate their\u00a0feature development\u00a0with\u00a0Azure Synapse.<\/p>\n

\u201cIn our current environment, we would have needed hundreds of custom scripts to validate and promote changes across our test and production environments. We\u2019re excited to now simply use SSDT, MSBuild, and the Publish task in Azure DevOps to deploy and release features to production on a consistent and faster cadence.\u201d –<\/em>\u00a0Anthony Sabol, Director, Reporting & Analytics at T-Mobile.<\/p><\/blockquote>\n

Integrate with Microsoft Azure Repos for continuous integration<\/span>\u00a0<\/span><\/h2>\n

Data engineers and developers can\u00a0<\/span>easily integrate their SQL Server Data Tool<\/span>s<\/span> database projects <\/span>with Microsoft <\/span>Azure Repos<\/span>.<\/span>\u00a0<\/span><\/p>\n

\"Using<\/p>\n

Configure continuous deployment using Microsoft Azure Pipelines<\/span>\u00a0<\/span><\/h2>\n

Changes committed to source control\u00a0<\/span>in Azure Repos <\/span>can automatically\u00a0<\/span>be\u00a0<\/span>pre-validated<\/span>\u00a0using\u00a0MSBuild\u00a0and\u00a0<\/span>promoted to\u00a0<\/span>target<\/span> environments using Microsoft Azure <\/span>Pip<\/span>e<\/span>lines<\/span>\u00a0and the\u00a0<\/span>built-in\u00a0<\/span>SQL\u00a0<\/span>Analytics<\/span>\u00a0<\/span>deployment\u00a0<\/span>task<\/span>\u00a0extension<\/span><\/a>.\u00a0<\/span>\u00a0<\/span><\/p>\n

\"Downloading<\/p>\n

Cross platform support for S<\/span>chema\u00a0<\/span>C<\/span>ompare\u00a0<\/span>with<\/span>\u00a0Azure Data Studio<\/span>\u00a0<\/span><\/h2>\n

Azure Data Studio<\/span><\/a>\u00a0is a cross-platform database tool<\/span> that<\/span>\u00a0now allows you to c<\/span>ompare the schema\u00a0<\/span>between two<\/span>\u00a0data\u00a0<\/span>warehouse definition<\/span>s<\/span>.\u00a0<\/span>\u00a0<\/span><\/p>\n

\"Using<\/p>\n

Next steps<\/h2>\n