Reporting with SQL Server Analysis Services

SQL Server Analysis Services (SSAS) provides robust capabilities for creating and managing data models that power rich reporting solutions. Whether you're using multidimensional cubes or tabular models, SSAS enables users to explore data, identify trends, and make informed business decisions.

Reporting Tools Integration

SSAS integrates seamlessly with various Microsoft reporting tools and third-party applications. The primary tools for interacting with SSAS data models for reporting include:

  • SQL Server Reporting Services (SSRS): A comprehensive platform for creating, deploying, and managing paginated reports and mobile reports.
  • Power BI: A powerful business analytics service that enables interactive visualizations and business intelligence capabilities with an interface simple enough for end users to create their own reports and dashboards.
  • Excel: Users can connect to SSAS models using Excel's PivotTable and PivotChart features for ad-hoc analysis and reporting.
  • Third-Party Tools: Many other BI and data visualization tools offer connectors for SSAS models.

Reporting with Multidimensional Models

Multidimensional models are built using OLAP (Online Analytical Processing) technology. They represent data in cubes, allowing for fast queries across multiple dimensions. Key concepts for reporting include:

  • Measures: Numerical values that can be aggregated (e.g., Sales Amount, Quantity).
  • Dimensions: Attributes used to slice and dice data (e.g., Time, Product, Geography).
  • Hierarchies: Structured drill-down paths within dimensions (e.g., Year > Quarter > Month).
  • MDX (Multidimensional Expressions): A query language used to retrieve data from multidimensional models.

Example MDX Query:


SELECT
    [Measures].[Sales Amount] ON COLUMNS,
    [Date].[Calendar Year].MEMBERS ON ROWS
FROM [Adventure Works]

Reporting with Tabular Models

Tabular models store data in memory using a relational in-memory database. They are often simpler to develop and manage than multidimensional models and are highly performant. Key concepts for reporting include:

  • Tables and Columns: Data is organized in tables with relationships defined between them, similar to a relational database.
  • Measures: Defined using DAX (Data Analysis Expressions).
  • Relationships: Define how tables are connected.
  • DAX (Data Analysis Expressions): A formula language used to create measures and calculated columns.

Example DAX Measure:


Total Sales = SUM('Sales'[SalesAmount])

Best Practices for Reporting

  • Design for User Needs: Understand the reporting requirements and tailor models accordingly.
  • Optimize Performance: Ensure models are designed for efficient querying.
  • Implement Security: Use row-level and object-level security to control data access.
  • Document Models: Provide clear documentation for business users and report developers.