Security in SQL Server Analysis Services Multidimensional Models

Implementing robust security is critical for any data solution. SQL Server Analysis Services (SSAS) Multidimensional Models provide a comprehensive set of features to control access to data at various levels, ensuring that users only see the information they are authorized to access.

Security Overview

SSAS security is primarily role-based. You define roles, grant specific permissions to these roles, and then assign users or Windows groups to these roles. This allows for granular control over what data and metadata users can view and interact with.

Roles

Roles are the cornerstone of SSAS security. Each role represents a group of users with similar access requirements. Roles can be defined at the server level, database level, or cube level. Within each role, you can specify:

Database Permissions: Control read, read definition, or full control over an Analysis Services database.
Object Permissions: Define access to specific objects like cubes, dimensions, and perspectives. You can grant read, read definition, or deny access.
Cell Security: Restrict access to specific data cells within a cube based on user membership in a dimension role.
Administrative Permissions: Grant roles administrative privileges over Analysis Services.

Permissions

Permissions dictate what actions a user or role can perform. Common permissions include:

Read: Allows users to query data from cubes and dimensions.
Read Definition: Allows users to view the metadata of objects but not query data.
Full Control: Grants complete administrative control over objects.
Read Data: Specific permission to read data.
Read Security: Allows users to view security settings.

Types of Security

SSAS Multidimensional Models support several types of security:

Server-Level Security: Managed through SSAS server roles, granting administrative rights.
Database-Level Security: Defines access to the entire Analysis Services database and its contents.
Object-Level Security: Granular control over individual cubes, dimensions, measures, hierarchies, and other objects.
Cell-Level Security: The most granular level, restricting access to individual data cells based on user membership in dimension roles. This is often implemented using RLS (Row-Level Security) concepts adapted for multidimensional data.
Custom Security: Through custom code or stored procedures, although this is less common and more complex to manage.

Best Practices

To ensure effective and maintainable security, consider these best practices:

Principle of Least Privilege: Grant only the necessary permissions required for users to perform their tasks.
Use Windows Groups: Assign Windows security groups to SSAS roles instead of individual users. This simplifies management when users join or leave teams.
Regular Audits: Periodically review role assignments and permissions to ensure they are still appropriate.
Document Your Security Model: Maintain clear documentation of your roles, their members, and the permissions granted.
Leverage Dimension Security for Data Restriction: Use dimension security to filter data visibility based on attribute values (e.g., restricting sales managers to see data only for their region).
Test Thoroughly: After implementing security changes, test them thoroughly from the perspective of different user roles.

For detailed information on configuring security in SQL Server Management Studio (SSMS) and best practices, refer to the official Microsoft documentation.

Example: Creating a Cube Read-Only Role

Here's a conceptual outline of how you might create a role to allow users to read data from a specific cube:

CREATE ROLE [CubeReadOnly]
GO

GRANT READ ON CUBE [YourCubeName] TO [CubeReadOnly]
GO

ALTER ROLE [CubeReadOnly] ADD MEMBER [YourDomain\YourGroup]
GO

This SQL Server Analysis Services scripting language (XMLA) snippet demonstrates granting read permission on a cube to a role and then adding a Windows group to that role. Actual implementation might involve using SSMS GUI or more complex XMLA.

MSDN Documentation