This project presents the design and implementation of an enterprise-style multidimensional OLAP cube created in SQL Server Analysis Services (SSAS) using the AdventureWorksDW database.
The solution focuses on multidimensional data modeling, analytical processing, KPI implementation, perspectives configuration, and interactive business intelligence reporting.
- OLAP cube development in SSAS
- Multidimensional data modeling
- Fact and dimension table integration
- KPI implementation and analysis
- Perspectives configuration
- Cube browsing and analytical reporting
- Business-oriented data exploration
- Hierarchy and relationship management
- FactInternetSales
- Customer
- Product
- Promotion
- Currency
- Sales Territory
- Date
- Order Date
- Ship Date
- Sales Amount
- Order Quantity
- Unit Price
- Discount Amount
- Freight
- Tax Amount
- Total Product Cost
The project includes a KPI named:
The KPI compares Sales Amount against a predefined business goal and visualizes performance status and trends within the OLAP environment.
A dedicated analytical perspective was created to simplify business-oriented reporting and improve cube usability.
The cube was processed and tested using the SSAS Browser interface to analyze:
- Sales by product categories
- Sales performance across years
- KPI evaluation
- Aggregated business metrics
The project uses the AdventureWorksDW sample database provided by Microsoft for data warehousing and business intelligence practice.
AdventureWorks is a widely used enterprise-style dataset for OLAP, SSAS, and multidimensional modeling exercises.
- SQL Server Analysis Services (SSAS)
- Microsoft SQL Server
- SQL Server Data Tools (SSDT)
- Visual Studio
- AdventureWorksDW Database
- OLAP / Multidimensional Modeling
The goal of this project is to demonstrate practical skills in multidimensional database design, OLAP cube processing, KPI implementation, and business intelligence analysis using Microsoft technologies.
The solution successfully demonstrates:
- Cube deployment and processing
- Dimension integration
- KPI configuration
- Perspective creation
- Interactive multidimensional analysis
- Business data aggregation and reporting
Paulina Broda