Multidimensional Models

Multidimensional models in SQL Server Analysis Services (SSAS) are a powerful way to organize and analyze data using a multidimensional cube structure. This approach is ideal for business intelligence scenarios where users need to explore data from various perspectives.

Understanding the Core Concepts

Multidimensional models are built upon several key concepts:

• Cubes: A central repository of data that contains measures (numeric values) and dimensions (categories for slicing and dicing the data).
• Dimensions: Represent descriptive attributes of the data, such as Time, Geography, or Products. Each dimension has hierarchies that allow users to drill down or roll up through different levels of granularity.
• Measures: Numeric values that represent business metrics, such as Sales Amount, Quantity Sold, or Profit. Measures are typically aggregated using standard aggregation functions like SUM, COUNT, AVERAGE, MIN, and MAX.
• Hierarchies: Ordered sets of attributes within a dimension that define relationships and enable drill-down/roll-up analysis. For example, a Time dimension might have a hierarchy of Year -> Quarter -> Month -> Day.
• Kpis (Key Performance Indicators): Specific measures that are tracked against defined goals or targets.

Creating a Multidimensional Model

The process of creating a multidimensional model typically involves the following steps:

1. Data Source View: Define the connection to your data sources and create a logical view of the data.
2. Dimension Design: Create and configure dimensions, defining their attributes and hierarchies.
3. Cube Design: Define the measures and link dimensions to the cube.

Example Cube Structure

Consider a sales cube. The dimensions might include:

• Date: With hierarchies for Year, Quarter, Month, Day.
• Product: With hierarchies for Category, Subcategory, Product Name.
• Geography: With hierarchies for Country, State, City.

The measures could be:

• Sales Amount (SUM)
• Quantity Sold (SUM)
• Average Selling Price (AVERAGE)

Advantages of Multidimensional Models

• Performance: Optimized for fast query performance due to pre-aggregation and specialized storage.
• Flexibility: Supports complex analytical queries and sophisticated calculations.
• Rich User Experience: Provides intuitive drill-down, roll-up, and slice-and-dice capabilities for business users.

Key Technologies and Tools

• SQL Server Data Tools (SSDT): The primary tool for designing, developing, and deploying SSAS multidimensional models.
• MDX (Multidimensional Expressions): The query language used to retrieve data from multidimensional cubes.

Further Reading

• Official Microsoft Documentation on Multidimensional Modeling
• MDX Language Reference