Microsoft Power BI is a great tool for data visualization, and designing reports, charts, and dashboards. Such an environment can also be referred to as a Multi-Tenant Environment, which means that a single Power BI instance serves multiple independent organizations or tenants. Each tenant here must have a private space to keep the data and reports of their company private.
At Code Creators, we help organizations implement secure, scalable analytics environments through expert Power BI consulting. Whether you're a software vendor, enterprise, or service provider managing multiple clients, working with an experienced Power BI consultant ensures your multi-tenant architecture is both efficient and secure. In this article, we’ll explore the key challenges and solutions involved in deploying Power BI in a multi-tenant setup.
Reasons for Multi-Tenant Power BI:
• Software Vendors: Offer Power BI reports as part of their service, by showing only their data to each customer.
• Large Corporations: Manage Power BI centrally but separate data for different departments.
• Service Providers: Deliver data analytics to multiple clients.
• Cost Efficiency: Sharing infrastructure can also be cost-effective in some instances.
• Central Management: Provides single point updates and declarations and security.
Main Problem:
One of the primary issues is the segregation of data (one tenant not to see another's data) and also segregation of content (one tenant's reports will not be seen by another).
Some of the main challenges include:
• Security and Data Leakage: Preventing data belonging to one tenant from being shown to another tenant.
• Performance and Scalability: Keeping the system fast and responsive with many simultaneous tenants.
• Tenant-Specific Customization: Different reports or branding for each tenant without having too many copies.
• Data Refresh Management: Updating data for many tenants efficiently without stressing the system.
•User Management and Authentication: Preventing users from accessing another tenant's content.
•Cost Management: Monitoring tenant usage to bill.
•Deployment and Lifecycle: Staging to deploy or update features across tenants.
Solutions for Multi-Tenant Power BI Deployment:
Power BI has several features and patterns, which are determined based on specific needs.
Solution 1: Row-Level Security (RLS) for Data Isolation
• Overview: RLS restricts the data a user sees in a report based on the user's identity.
• How it works: One Power BI data model holds the information of different tenants along with a column of "Tenant ID". RLS rules (based on DAX) present data only when "Tenant ID" equals that of the logged-in user. Logins are routed to their Tenant ID.
• Challenges Addressed: Security and Data Leakage.
• Limitations:
O Content Segregation: Filters data rows, not hides reports themselves.
O Complexity: Difficult to manage with lots of tenants.
o Performance: May affect performance with big datasets.
o No Customization: The same report layout is viewed by all tenants.
Solution 2: Workspaces for Content Segregation
• Overview: A "workspace" in Power BI Service structures reports, dashboards, and datasets. There is one workspace for each tenant.
• How it works: Each tenant is assigned a separate Power BI workspace. Their reports, dashboards, and datasets are published to only their workspace. Users are given access only to their own workspace.
• Challenges Addressed: Content Separation, Security.
• Limitations:
o Isolation of Data: Does not address data isolation if shared underlying datasets (still requires RLS).
O Overhead in Management: It can be complicated to manage multiple workspaces.
O Replication of Data: Can cause replicated data and wasteful refresh if not shared datasets.
Solution 3: Power BI Embedded for Application Integration
• Overview: Power BI Embedded places reports right into your own apps. Users work with reports in your app, not within Power BI Service.
•How it works: You utilize Power BI Premium or Fabric capacity. Your application code calls into Power BI Embedded APIs to render reports. Your app manages user logins and informs Power BI Embedded what data (through RLS) and reports the user can see. Users never log directly into Power BI Service.
• Solved Challenges: Security, Content Segregation, Performance, Scalability, Tenant-Specific Customization.
• Limitations:
O Developer Effort: Demands a lot of integration effort.
O Cost: Premium/Fabric capacity is costly.
O Complexity: More complicated setup than sharing reports in Power BI Service.
Solution 4: Dataflows for Centralized Data Preparation
• Overview: Dataflows prepare and transform data once for reuse in numerous Power BI datasets.
• How it works: Dataflows are connected to raw data, cleaning, and transformation. They can bring in tenant-specific data or can bring in all and filter afterward. Such cleaned data can be consumed by various Power BI datasets.
• Addressed Challenges: Data Refresh Management, Performance, and Reducing Data Duplication.
• Limitations:
oDoes not bypass RLS or employ different datasets for final data clearance.
oCauses additional architectural overhead.
Solution 5: Azure Active Directory (Azure AD) for User Management
• Overview: Azure AD is an identity and access management service in the cloud from Microsoft for the purpose of user verification and authorization management.
• How it works: The users for each tenant are hosted in their Azure AD. Power BI also logs into Azure AD. Security groups may be utilized for RLS or workspace permission.
• Solved Challenges: User Management and Authentication, Security.
• Constraints: Foundation service; not all multi-tenant challenges are solved by itself, but required for others.
Integration Solutions for Robust Multi-Tenant Deployments:
Most multi-tenant Power BI deployments are combinations of several solutions in practice:
• Power BI Embedded is the one that most vendors turn to when developing customer-facing reports, as it is more controlled.
• Row-Level Security (RLS) is critical within Power BI Embedded, ensuring that each client can only see their data.
• Workspaces are for report template organization or segregation of content for internal divisions.
• Dataflows are preparers for shared data and sharing.
• Azure AD remains the ultimate body for both authentication and access.
Streamlining Deployment Workflow (Software Vendor Example):
Central Data Repository: Each and every customer information is in a central database with the Tenant ID attached.
2. Data Preparation (Opt.): Develop Dataflows to prepare raw data.
3. The Power BI Core Report Template: Create one Power BI Desktop file with RLS rules based on Tenant ID.
4. Publish to Power BI Service: Publish the master template to a Power BI workspace.
5. Provisioning/Datasets: For new tenants, create new datasets from the template (with RLS), or use a single dataset with dynamic RLS in Embedded.
6. Assign Power BI Premium/Fabric Capacity Workspaces: Workspaces to dedicated capacity for better performance.
7. Application Embed: Your application embeds Power BI reports. During user log-in, your app makes available their Tenant ID to Power BI Embedded.
8. Dynamic RLS: Power BI Embedded applies RLS rules to display only the user's applicable data.
9. User Experience: The customer views their own data in your application, without actually using Power BI Service.
Conclusion
The deployment of Power BI in a multi-tenant system calls for measures to isolate tenant data and separate their reports. The issues to be addressed are related to data security, performance, customization, data refresh, user access, and cost.
Power BI offers several solutions for this purpose, including Row-Level Security (RLS) for data filtering, Workspaces for separating content, and Power BI Embedded for application embedding. Data preparation is simplified through dataflows, and Azure AD secures authentication.
Utilizing these solutions helps form secure and efficient multi-tenant Power BI systems. That way, each tenant only sees their data, therefore ensuring privacy and integrity while securely sharing the environment.
