Deploy and Process Azure Analysis Services Models

This document outlines the steps and considerations for deploying Analysis Services models to your Azure Analysis Services instance and processing the data within them.

Deployment Methods

You can deploy your Analysis Services models using various tools and methods:

1. Visual Studio with SQL Server Data Tools (SSDT)

Visual Studio with SSDT is the primary development environment for Analysis Services models. After developing your model, you can directly deploy it to your Azure Analysis Services instance.

1. Open your Analysis Services project in Visual Studio.
2. Right-click on the project and select Properties.
3. Under the Deployment tab, configure the Server Name to your Azure Analysis Services instance URI (e.g., asazure://yourregion.asazure.windows.net/yourservername).
4. Set the Database Name for the new database.
5. Right-click on the project again and select Deploy.

2. Tabular Editor

Tabular Editor is a popular third-party tool that provides a powerful and flexible way to work with tabular models. It supports deploying models directly to Azure Analysis Services.

1. Connect to your Azure Analysis Services instance using Tabular Editor.
2. Open your local model file or clone an existing database.
3. Make your desired changes.
4. Use the Deploy to Azure Analysis Services option.

3. TOM (Tabular Object Model) and PowerShell

For automation, you can use the Tabular Object Model (TOM) library or PowerShell scripts to deploy your model programmatically.

A basic PowerShell script to deploy might look like this:

# Connect to Azure Analysis Services
$Server = New-Object Microsoft.AnalysisServices.Tabular.Server
$Server.Connect("asazure://yourregion.asazure.windows.net/yourservername")

# Deploy the model (assuming you have a database object)
$Database = New-Object Microsoft.AnalysisServices.Tabular.Database
$Database.Name = "YourModelDatabase"
# ... configure database properties ...
$Server.Databases.Add($Database)
$Server.Update()
            

Data Processing

Once your model is deployed, you need to process the data to load it into the tabular model. Azure Analysis Services supports several processing modes:

Processing Modes:

• Full Process: Clears all existing data and reprocesses all objects in the model. Use this when you have significant schema changes or need a complete data refresh.
• Clear Process: Clears all data from the specified objects without reprocessing them. This is typically followed by a subsequent process operation.
• Data Only Process: Reprocesses only the data within the specified tables. It does not affect metadata or relationships.
• Incremental Process: Reprocesses only new or changed data within specified tables. This is highly efficient for large datasets that are updated frequently.

Processing Methods:

1. Visual Studio

You can initiate processing directly from Visual Studio after deployment:

1. In Solution Explorer, right-click on the Analysis Services database.
2. Select Process....
3. Choose the objects you want to process and select the desired processing mode.
4. Click Process.

2. SQL Server Management Studio (SSMS)

SSMS provides a user-friendly interface for managing and processing your Azure Analysis Services database.

1. Connect to your Azure Analysis Services instance in SSMS.
2. Right-click on the database and select Process....
3. Configure processing options and click OK.

3. PowerShell and Analysis Services Cmdlets

Automate processing using PowerShell with the Microsoft.AnalysisServices.PowerShell.Cmdlets module.

# Example: Full process a table
Process-AAServerDatabase -Server "asazure://yourregion.asazure.windows.net/yourservername" -DatabaseName "YourModelDatabase" -TableName "DimProduct" -ProcessingMode "Full"
            

4. Azure Portal

The Azure portal offers basic processing capabilities for tables directly from the server's management interface.

1. Navigate to your Azure Analysis Services resource in the Azure portal.
2. Under Model, select Tables.
3. Choose the table(s) you want to process, click Process, and select the mode.

5. REST API

For advanced automation and integration, you can use the Analysis Services REST API to trigger processing operations.

Automation and Scheduling

To ensure your data is always up-to-date, consider automating your deployment and processing tasks. Azure Data Factory or Azure Logic Apps can be used to schedule these operations based on your requirements.

Azure Data Factory:

You can use Azure Data Factory pipelines with activities like the 'Azure Analysis Services Processing' task or custom scripts to orchestrate deployments and processing.

Azure Logic Apps:

Logic Apps can be triggered by events or schedules to execute PowerShell scripts or call the Analysis Services REST API for automated management.