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Security in Analysis Services

This document provides a comprehensive overview of security considerations and implementation strategies for Microsoft SQL Server Analysis Services.

Introduction to Analysis Services Security

Securing your Analysis Services (SSAS) environment is crucial to protect sensitive business intelligence data. Analysis Services provides a robust set of security features that allow you to control access at various levels, from the server itself down to individual cells within a cube. This document will guide you through the key security concepts, including authentication, authorization, roles, and best practices.

Authentication and Authorization

Analysis Services supports two primary security models:

  • Windows Authentication: Utilizes the identities of Windows users and groups. This is the recommended and most common method for on-premises deployments.
  • Custom Authentication: Allows for integration with custom security providers or Active Directory Federation Services (AD FS) for scenarios like cloud deployments or federated identity.

Authorization is the process of determining what authenticated users or groups are allowed to do. In Analysis Services, this is managed through roles.

Roles in Analysis Services

Roles are fundamental to managing access to Analysis Services objects. You can define roles at the server level or database level.

Server Roles

Server roles grant administrative privileges over the entire Analysis Services instance.

  • Server Administrator: Full control over the Analysis Services instance, including managing databases, creating and deleting objects, and managing other server roles.

Database Roles

Database roles define permissions on databases and their contained objects (cubes, dimensions, mining structures, etc.).

  • Database Administrator: Full control over a specific database, including managing its objects and database roles.
  • Full Control: Allows read and write access to all objects within the database.
  • Read Definition: Allows users to view the metadata (definitions) of objects but not the data.
  • Read Data: Allows users to query and retrieve data from objects like cubes and dimensions.
  • Custom Roles: You can define custom roles with granular permissions tailored to specific user groups or application needs.

Creating and Managing Roles

Roles are typically managed using SQL Server Management Studio (SSMS) or programmatically using XMLA (XML for Analysis) or AMO (Analysis Management Objects).

Example: Creating a Read-Only Role using AMO (C#)


using Microsoft.AnalysisServices.Common;
using Microsoft.AnalysisServices.Tabular; // For Tabular models
// using Microsoft.AnalysisServices.Cube; // For Multidimensional models

// ... connection to Analysis Services server ...

Database db = server.Databases.GetByName("YourDatabaseName");
Role readOnlyRole = db.Roles.Add("ReadOnlyUsers");
readOnlyRole.Members.Add(new DirectMember("DOM\UserGroup")); // Add Windows group or user
readOnlyRole.DatabasePermissions = DatabasePermission.ReadData;
readOnlyRole.Update();

Object-Level Security

Beyond roles, you can implement finer-grained security at the object level:

  • Cube Security: Control access to specific cubes, dimensions, and measures.
  • Dimension Security: Restrict access to specific members of a dimension, allowing users to see only relevant data subsets. This is often achieved using dimension security roles.
  • Cell Security: The most granular level, allowing you to restrict access to individual cells within a cube based on user or role. This is implemented through custom logic or security-related measures.

Best Practices for SSAS Security

To ensure a secure Analysis Services deployment, consider the following best practices:

  • Principle of Least Privilege: Grant only the necessary permissions to users and roles. Avoid granting excessive privileges.
  • Use Windows Authentication: Whenever possible, leverage Windows authentication for seamless integration with your Windows environment.
  • Regularly Review Roles and Permissions: Periodically audit your roles and member assignments to ensure they are still appropriate and up-to-date.
  • Implement Row-Level Security (RLS) and Object-Level Security (OLS): Utilize dimension security and cell security features to enforce data segregation.
  • Secure the Underlying Data Sources: Ensure that the data sources used by Analysis Services are also adequately secured.
  • Monitor and Audit: Implement logging and monitoring to detect suspicious activity.
  • Use Strong Passwords and Account Management: If custom authentication is used, enforce strong password policies.
  • Keep SSAS Updated: Apply the latest security patches and updates for Analysis Services.

Important Consideration:

For Tabular models, security can also be managed using the DAX expression language and roles defined within the model itself, often integrated with Azure Active Directory for cloud scenarios.

Conclusion

Effectively implementing security in Analysis Services requires a thorough understanding of its features and careful planning. By leveraging roles, object-level security, and adhering to best practices, you can safeguard your valuable business intelligence data and ensure that users have access only to the information they are authorized to see.

Further Reading: