Processing and Deployment

This section covers the essential steps involved in processing and deploying your SQL Server Analysis Services (SSAS) multidimensional models. Effective processing ensures data accuracy and freshness, while proper deployment makes your models accessible to users and applications.

Understanding Processing

Processing is the act of loading data into your Analysis Services objects (databases, cubes, dimensions, measures, etc.) and calculating derived values. The type of processing depends on whether the object has been processed before and the nature of the data changes.

Processing Modes

Process Default: This is the most common mode. Analysis Services determines the appropriate processing action based on the object's current state and whether it has been processed before. It will perform a full process if the object has never been processed, or a specific incremental or re-process as needed.
Process Full: This mode completely rebuilds the object, including all its dependent objects. It's a good option for a clean slate but can be time-consuming for large models.
Process Add: This mode adds new data to existing partitions without affecting previously processed data. It's useful for incremental loads.
Process Update: This mode updates existing data within processed partitions.
Process Recalc: This mode re-calculates aggregations and other derived values without reloading the base data. Useful after schema changes or when only calculations need refreshing.
Process Clear: This mode removes all data from the object, leaving the structure intact. It does not remove related objects.
Process Data: This mode loads only the data into the object, leaving aggregations and other structures unprocessed.
Process Index: This mode rebuilds the internal structures (like hash indexes) used for query performance.

Processing Strategies

When planning your processing, consider the following:

Full Processing: The simplest but most resource-intensive. Suitable for initial loads or when data integrity is a concern.
Incremental Processing: Processes only new or changed data since the last processing operation. Requires careful setup of partition schemes and often involves batch processing.
Parallel Processing: Processing multiple objects simultaneously to reduce overall processing time. SSAS can automatically leverage this if configured correctly.
Scheduled Processing: Automating processing tasks using SQL Server Agent jobs or other scheduling tools.

Deployment Options

Deploying your Analysis Services model makes it available for querying. You can deploy from your development environment (e.g., SQL Server Data Tools - SSDT) to a target Analysis Services instance.

Deployment Methods

Deployment from SSDT: The most common method. After developing your model in SSDT, you right-click the project and select "Deploy". SSDT generates deployment scripts and executes them against the target server.
Using Analysis Management Objects (AMO): Programmatically deploy models using AMO, a .NET library. This is ideal for automated deployment pipelines.
Using XMLA scripts: Analysis Services uses XML for Analysis (XMLA) for many operations, including deployment. You can manually execute XMLA scripts or use them in automated processes.

Deployment Considerations

Target Server Configuration: Ensure the target Analysis Services instance is properly configured for your model's needs.
Database Permissions: Grant appropriate read permissions to users and applications that will query the deployed model.
Environment-Specific Settings: Use deployment configurations to manage differences between development, staging, and production environments (e.g., connection strings, server names).

Best Practices

Key Takeaways:

Understand the different processing modes and choose the most efficient one for your scenario.
Implement incremental processing for large, frequently updated datasets.
Automate processing tasks using SQL Server Agent or other schedulers.
Use SSDT for straightforward deployments and AMO/XMLA for advanced automation.
Test your processing and deployment procedures thoroughly.

Tools for Processing and Deployment

SQL Server Data Tools (SSDT): For model development, deployment, and basic processing tasks.
SQL Server Management Studio (SSMS): For managing Analysis Services instances, initiating manual processing, and executing XMLA scripts.
SQL Server Agent: For scheduling processing jobs.
AMO (Analysis Management Objects): For programmatic control over SSAS operations.
PowerShell: Can be used to interact with SSAS via AMO cmdlets or by executing scripts.

By mastering the concepts of processing and deployment, you can ensure your Analysis Services multidimensional models are accurate, up-to-date, and readily available to drive insightful business decisions.