Design and Development for SQL Server Analysis Services
This section provides comprehensive guidance on designing and developing solutions using SQL Server Analysis Services (SSAS). Whether you are building multidimensional models, tabular models, or working with data mining, you'll find the essential information here.
Understanding SSAS Models
Multidimensional Models
Multidimensional models, often referred to as OLAP cubes, provide a rich, hierarchical structure for data analysis. They are well-suited for complex business scenarios requiring deep dives into data.
- Creating Dimensions
- Defining Measures and Hierarchies
- Designing Cubes and Perspectives
- Implementing Calculations (MDX)
Tabular Models
Tabular models offer a simplified, in-memory approach to business intelligence. They use a relational data modeling paradigm and are powered by the VertiPaq engine, offering high performance and ease of use, especially for users familiar with Power BI and Excel.
- Designing Tables and Relationships
- Creating Calculated Columns and Measures (DAX)
- Implementing Row-Level Security
- Best Practices for Tabular Model Performance
Data Mining and Machine Learning
Leverage the data mining capabilities of SSAS to uncover hidden patterns, predict future trends, and gain actionable insights from your data.
- Introduction to Data Mining Concepts
- Creating Data Mining Models (Classification, Regression, Clustering, Association Rules)
- Using DMX (Data Mining Extensions)
- Integrating with Azure Machine Learning
Development Tools and Technologies
Learn about the primary tools and languages used for SSAS development.
SQL Server Data Tools (SSDT)
SSDT is the integrated development environment for building SSAS, SQL Server Reporting Services (SSRS), and SQL Server Integration Services (SSIS) projects. It provides a visual designer for model creation and management.
Key features include:
- Project-based development
- Visual designers for cubes, dimensions, and tables
- Deployment wizards
- Integration with source control
MDX (Multidimensional Expressions)
MDX is the query and programming language for multidimensional models. It's used for defining calculations, creating complex queries, and scripting.
Example of a simple MDX calculation:
CREATE MEMBER CURRENTCUBE.[Measures].[Internet Sales Amount] AS
[Internet Sales].[Sales Amount].MEMBERS,
FORMAT_STRING = "Currency",
VISIBLE = 1 , ASSOCIATED_MEASURE_GROUP = 'Internet Sales'
DAX (Data Analysis Expressions)
DAX is the formula expression language used primarily with tabular models and Power BI. It's designed for creating calculated columns, measures, and row-level security rules.
Example of a simple DAX measure:
Total Sales := SUM('Sales'[Sales Amount])
Best Practices
Follow these best practices to ensure your SSAS solutions are performant, scalable, and maintainable.
- Data Modeling Strategies
- Performance Optimization Techniques
- Security Design Considerations
- Testing and Validation Methods