Deploy, Process, and Query Multidimensional Models

 This document provides a comprehensive guide to the deployment, processing, and querying of multidimensional models in SQL Server Analysis Services (SSAS).

Once you have designed and developed your multidimensional model in SQL Server Data Tools (SSDT), the next crucial steps involve deploying the model to an Analysis Services instance, processing the data into the cubes, and then querying the data using various client applications. This section covers the essential concepts and procedures for each of these phases.

1. Deployment

Deployment is the process of publishing your Analysis Services project from SSDT to a target Analysis Services server. This makes your model available for users to connect to and query.

Steps for Deployment:

1. Open your SSAS Project: Ensure your multidimensional model project is open in Visual Studio with SQL Server Data Tools installed.
2. Configure Deployment Properties:
   • Right-click on the project in Solution Explorer and select 'Properties'.
   • In the Project Properties dialog, navigate to the 'Deployment' tab.
   • Set the 'Server Name' property to the name or IP address of your Analysis Services instance.
   • Specify the 'Database Name' for the deployed multidimensional database.
   • Configure 'Configuration settings' (e.g., Development, Test, Production) to manage different deployment environments.
3. Build the Solution: Right-click the project and select 'Build'. This compiles your project into deployable AMO objects.
4. Deploy the Solution: Right-click the project and select 'Deploy'. Visual Studio will connect to the specified Analysis Services server and create/update the multidimensional database.

2. Processing

Processing is the operation that loads data from your data sources into the multidimensional structures (cubes, dimensions, partitions). Without processing, your cubes will be empty and cannot be queried.

Processing Methods:

• Full Process: Deletes all existing data and metadata, then creates new structures and loads all data. This is the most comprehensive but also the slowest.
• Process Update: Processes only the necessary objects to reflect changes in the source data or metadata. This is generally faster than a full process for incremental updates.
• Process Add: Adds new data to existing structures without affecting existing data. Useful for appending new records.
• Process Recalcuate: Recalculates aggregated measures based on the existing data.

Processing Operations:

You can initiate processing through several means:

• SSDT: Right-click on a cube, dimension, or the entire database in Solution Explorer and select 'Process...'.
• SQL Server Management Studio (SSMS): Connect to your Analysis Services instance, right-click on the database, and select 'Process...'.
• SQL Server Management Objects (SMO) or AMO: Programmatically initiate processing using scripts or applications.
• SQL Server Agent Jobs: Schedule automated processing routines.

 Regularly scheduled processing jobs are essential for keeping your data cubes up-to-date. Consider using incremental processing where possible to reduce processing time.

3. Querying

Once deployed and processed, your multidimensional models can be queried using languages like Multidimensional Expressions (MDX) or Data Access Protocol (DAP). Client applications such as Excel, Power BI, Tableau, or custom applications can connect to the SSAS database.

Querying with MDX:

MDX is a powerful query language for multidimensional data. Here's a simple example to retrieve sales amounts for a specific year:

SELECT
    {[Measures].[Internet Sales Amount]} ON COLUMNS,
    {[Date].[Calendar Year].&[2023]} ON ROWS
FROM
    [Adventure Works DW2019]

Connecting with Client Applications:

• Excel: Use the "Get Data" feature and select "From Analysis Services". Provide the server name and connect to your database.
• Power BI: Utilize the "Connect to Analysis Services" option, specifying the server and database.
• SSMS: You can also execute MDX queries directly against the Analysis Services instance using the 'New Query' > 'MDX' option.

 Understanding the structure of your cubes, dimensions, and hierarchies is key to writing effective and performant MDX queries.

Example Query with Multiple Dimensions:

Retrieve sales amounts by product category and geography for a specific quarter:

SELECT
    {[Measures].[Internet Sales Amount]} ON COLUMNS,
    [Product].[Category].Members ON ROWS,
    [Geography].[Country].&[United States] ON PAGES
FROM
    [Adventure Works DW2019]
WHERE
    ([Date].[Calendar Quarter].&[2023 Q3])

This section covers the fundamental aspects of deploying, processing, and querying your SSAS multidimensional models. Effective utilization of these steps is critical for delivering valuable business insights to your users.