Deploying Analysis Services Solutions

Note: This tutorial guides you through the process of deploying a SQL Server Analysis Services (SSAS) solution from Visual Studio to a production environment. Ensure you have the necessary administrative privileges and understand your target SSAS server's configuration.

1. Introduction to Deployment

Deploying an Analysis Services solution involves taking your carefully designed multidimensional or tabular model and making it accessible to end-users and applications. This typically includes deploying the project from Visual Studio to an SSAS instance, configuring security, and setting up scheduled processing.

Common deployment scenarios include:

  • Deploying to a development or test environment for validation.
  • Deploying to a staging environment before moving to production.
  • Deploying directly to a production Analysis Services server.

2. Preparing Your Solution for Deployment

Before deploying, it's crucial to ensure your solution is ready. This might involve:

  • Configuration Files: Using deployment configurations in Visual Studio to manage differences between environments (e.g., database names, server names, connection strings).
  • Parameterization: Defining parameters for properties that might change upon deployment.
  • Testing: Thoroughly testing your model in a development or test environment.

In Visual Studio, you can manage configurations via the Solution Explorer:


Project Properties -> Configurations -> [Select Configuration]

Here, you can set different values for properties like TargetServer and TargetDatabase for each configuration (e.g., Debug, Release, Staging).

3. Deploying the Solution from Visual Studio

The most common method for deployment is directly from SQL Server Data Tools (SSDT) within Visual Studio.

  1. Open your SSAS project in Visual Studio.
  2. Right-click on the project name in Solution Explorer.
  3. Select Deploy.
  4. In the Deployment Wizard, select the desired SSAS server instance and database name. You can use the properties defined in your deployment configurations.
  5. Follow the wizard prompts to complete the deployment.

Alternatively, you can deploy by right-clicking the project and choosing Properties, then navigating to the Deployment tab. Here, you can specify the server and database names.

Tip: For automated deployments, consider using Visual Studio's project deployment models or integrating with tools like Azure DevOps or SQL Server Management Objects (SMO).

4. Using Deployment Wizard and Configurations

The deployment wizard simplifies the process. When you initiate deployment, it prompts for key settings. Leveraging configurations is essential for managing multiple environments.

Example Deployment Configuration:


<?xml version="1.0" encoding="utf-8"?>
<Project ToolsVersion="15.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
  <PropertyGroup>
    <Configuration Condition=" '$(Configuration)' == '' ">Debug</Configuration>
    <SchemaVersion>2.0</SchemaVersion>
    <ProjectGuid>YOUR-GUID-HERE</ProjectGuid>
    <...(other properties).../>
  </PropertyGroup>
  <PropertyGroup Condition=" '$(Configuration)|$(Platform)' == 'Debug|AnyCPU' ">
    <PlatformTarget>AnyCPU</PlatformTarget>
  </PropertyGroup>
  <PropertyGroup Condition=" '$(Configuration)|$(Platform)' == 'Release|AnyCPU' ">
    <PlatformTarget>AnyCPU</PlatformTarget>
    <TargetServer>YourDevServer</TargetServer>  <!-- Overridden in other configs -->
    <TargetDatabase>AdventureWorksDW_Dev</TargetDatabase> <!-- Overridden in other configs -->
  </PropertyGroup>
  <PropertyGroup Condition=" '$(Configuration)|$(Platform)' == 'Staging|AnyCPU' ">
    <PlatformTarget>AnyCPU</PlatformTarget>
    <TargetServer>YourStagingServer</TargetServer>
    <TargetDatabase>AdventureWorksDW_Staging</TargetDatabase>
  </PropertyGroup>
  <!-- ... (other PropertyGroups for configurations) ... -->
</Project>

In Visual Studio, you would set the Active Solution Configuration to "Staging" and then deploy. The properties defined for the "Staging" configuration will be used.

5. Post-Deployment Steps

After a successful deployment, consider these crucial steps:

  • Security Configuration: Assign appropriate roles and permissions to users and groups on the deployed database using SQL Server Management Studio (SSMS).
  • Database Processing: Schedule regular processing of your SSAS database to ensure data is up-to-date. This can be done via SQL Server Agent jobs, SSIS packages, or AMO/TOM scripting.
  • Validation: Connect to the deployed database from a client tool (e.g., Excel, Power BI, Reporting Services) to verify the model is accessible and functioning as expected.

You can process the database directly from Visual Studio after deployment or using SSMS.

6. Advanced Deployment Techniques

For more complex scenarios, explore:

  • SQL Server Management Objects (SMO): Programmatically control SSAS objects and deployments.
  • SQL Server Integration Services (SSIS): Use SSIS to orchestrate deployment, processing, and data loading tasks.
  • Scripting: Generate deployment scripts using Tabular Object Model (TOM) or Multidimensional Object Model (MOM).
  • Azure Analysis Services: If deploying to Azure, follow specific connection and deployment guidelines for the cloud service.

This guide provides a foundational understanding of deploying Analysis Services solutions. For more in-depth information and specific scenarios, refer to the official Microsoft documentation and community resources.