MSDN Documentation

Dashboard Integration with SQL Server Analysis Services

This tutorial guides you through the process of integrating Microsoft SQL Server Analysis Services (SSAS) with various business intelligence dashboard tools. Analysis Services provides a powerful analytical engine for multidimensional and tabular data, enabling rich insights and performance for your business applications.

By connecting your dashboards directly to SSAS, you can leverage pre-aggregated data, complex calculations, and robust security models, leading to faster query performance and a more scalable analytical solution.

Prerequisites

Before you begin, ensure you have the following:

• A working SQL Server Analysis Services instance (either Multidimensional or Tabular mode).
• A deployed SSAS database with a well-defined model (cubes, dimensions, measures, or tabular models).
• Access credentials to the SSAS instance.
• A dashboarding tool of your choice. Popular options include:
  • Power BI
  • Tableau
  • Qlik Sense
  • Excel (using Power Pivot or Get & Transform Data)
  • Custom web applications using client libraries
• Basic understanding of your SSAS data model, including dimensions, hierarchies, and measures.

Integration Steps

Step 1: Prepare Your Analysis Services Model

Ensure your SSAS model is optimized for reporting. This includes:

• Well-defined Measures: Create meaningful measures that aggregate your business data.
• Hierarchies: Define user-friendly hierarchies for dimensions (e.g., Time: Year > Quarter > Month, Geography: Country > State > City).
• KPls (Key Performance Indicators): Define KPIs within SSAS for critical business metrics.
• Security: Implement appropriate row-level or object-level security if needed.
• Performance Tuning: Optimize queries and partitions for faster retrieval.

Step 2: Connect to Analysis Services from Your Dashboard Tool

The exact steps vary by tool, but the general process involves selecting "Connect to Data" or a similar option and choosing "SQL Server Analysis Services" as the data source.

You will typically need to provide:

• Server Name: The name or IP address of your SSAS server.
• Authentication: Choose the appropriate authentication method (Windows Authentication or specific credentials).
• Database/Model: Select the specific SSAS database or model to connect to.

Most tools offer two connection modes:

• Import: Data is imported into the dashboard tool's internal engine. This offers faster performance but requires scheduled refreshes.
• DirectQuery/Live Connection: Queries are sent directly to SSAS in real-time. This provides the most up-to-date data but performance depends heavily on the SSAS model and network latency.

Step 3: Create Measures and KPIs

Once connected, you can directly use the measures and KPIs defined in your SSAS model within your dashboard visualizations.

If your tool supports it, you can also create calculated measures or KPIs within the dashboard tool that build upon the existing SSAS measures. For example, you might calculate a Year-over-Year growth percentage using an SSAS "Sales Amount" measure.

Step 4: Design Your Dashboard Layout

Arrange your visualizations (charts, tables, cards) to tell a compelling story with your data. Group related information together and ensure a logical flow.

Utilize the dimensions and hierarchies from your SSAS model to build interactive filters and slicers, allowing users to drill down and explore data at different levels of granularity.

Step 5: Implement Interactivity

Enhance user experience by enabling interactivity between dashboard elements:

• Cross-filtering: When a user selects an item in one visualization (e.g., a specific country), other visualizations automatically filter to show data relevant to that selection.
• Drill-down/Drill-up: Leverage SSAS hierarchies to allow users to navigate through different levels of detail.
• Tooltips: Configure tooltips to display additional relevant information when a user hovers over a data point.

For custom web applications, you can use client-side libraries (like JavaScript APIs for Power BI Embedded or custom SSAS OData connectors) to programmatically control dashboard behavior.

Step 6: Deployment and Refresh

Deployment: Share your dashboard with stakeholders. This might involve publishing to a Power BI service, a Tableau Server, or embedding it within a web portal.

Data Refresh:

• Import Mode: Schedule regular data refreshes to keep the dashboard data up-to-date. This is configured within the dashboard tool's data gateway or service.
• DirectQuery/Live Connection: Data is inherently live. Ensure the SSAS server is accessible and performing well.

For SSAS Multidimensional models, consider using the XMLA endpoint for efficient querying from compatible tools.

Best Practices

• Model Design First: A robust and well-designed SSAS model is paramount.
• Use Live Connection/DirectQuery When Possible: For real-time data needs, but ensure SSAS performance is adequate.
• Leverage SSAS Hierarchies: For intuitive drill-down capabilities.
• Define KPIs in SSAS: For consistent business metric definitions.
• Optimize SSAS Performance: Use query tuning, indexing, and partitioning.
• Understand Data Latency: Be clear about how fresh the data is, especially with import modes.
• Secure Your Data: Implement SSAS security features effectively.
• Keep Dashboard Tools Updated: Benefit from the latest features and performance improvements.

Troubleshooting Common Issues

• Connection Errors: Verify server name, credentials, and firewall rules. Ensure SSAS is running and accessible.
• Slow Performance: Check SSAS model optimization, query execution plans, and network latency. Consider migrating to DirectQuery if using import.
• Incorrect Data: Review SSAS measure definitions, dimension relationships, and data loading processes. Ensure the correct SSAS database/model is selected.
• Security Issues: Confirm user permissions on SSAS and verify role assignments.

Consult the documentation for your specific dashboard tool and SSAS version for detailed troubleshooting steps.

Conclusion

Integrating SQL Server Analysis Services with your dashboarding tools unlocks the full potential of your business data. By following these steps and best practices, you can create powerful, performant, and insightful dashboards that drive better business decisions.

Experiment with different visualizations and interactivity options to create compelling analytical experiences for your users.