Technical Training
Analysis Services TrainingTable of Contents
MSAS - Building a Virtual Cube
MSAS - Building a Virtual Cube - Page 2
MSAS - Building a Virtual Cube - Page 3MSAS - Building a Virtual Cube Page - 3
MSAS - Building a Virtual Cube
Consolidation of data from multiple cubes into a Virtual cube
The sales information is contained in the Sales cube. The region details are contained in the region cube. Let us say we want to combine the two to obtain information on the sales made in different regions. A virtual cube can be used to compare the measures from the different cubes.
Right click the cubes folder, and click New Virtual cube. Click Next on the welcome screen. In the list of available cubes click Sales and Region.
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Click Next. In the measures list select the measures required. Then click the dimensions required from the Dimensions list and click next.
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Give a name to the virtual cube, Process the cube and view the data.
When measures are combined in virtual cubes for inclusion, the user must select a measure from each cube he wants to combine. The wizard automatically removes any cubes that do not have measures. Technically, it is possible to combine two cubes without a shared dimension, but none of the cells in the virtual cube will contain a value.
Analysis Services Training
- MSAS - Browsing the Dependency Network
- MSAS - Building a Relational Decision Tree Model
- MSAS - Introduction to Data Mining
- MSAS - Applying security to a Dimension
- Tutorial 65: MSAS - Managing Cube Roles
- MSAS - Understanding Database Roles
- MSAS - Securing User Authentication
- MSAS - Introducing Analysis Services Security
- MSAS - Writebacks
- MSAS - Defining and Creating Drillthrough
- MSAS - Defining and Creating Auctions
- MSAS - Creating and Maintaining Calculated Members in Virtual Cubes
- MSAS - Building a Virtual Cube
- MSAS - Understanding Virtual Cubes
- MSAS - Introducing Solve Order
- MSAS - Implementing Calculations Using MDX Part 2
- MSAS - Implementing Calculations Using MDX Part 1
- MSAS - Merging Partitions
- MSAS - Introduction and Managing Partitions
- MSAS - Troubleshooting Cube Processing
- MSAS - Optimizing Cube Processing
- MSAS - Processing Dimensions and Cubes
- MSAS - Introducing Dimension and Cube Processing
- MSAS: Optimization Tuning Part 2
- MSAS: Optimization Tuning Part 1
- MSAS: Usage-Based Optimization
- MSAS: Analysis Services Aggregations
- MSAS: The Storage Design Wizard
- MSAS: Analysis Server Cube Storage
- MSAS: Defining Cube Properties
- MSAS: Introduction and Working with Measures
- MSAS: Introduction and Working with Cubes
- MSAS: Virtual Dimensions
- MSAS: Introducing Member Properties
- MSAS: Creating Custom Rollups
- MSAS: Creating a Time Dimension
- MSAS: Understanding Hierarchies
- MSAS: Dimension Storage Modes and Levels
- MSAS: Working with Levels and Hierarchies
- MSAS: Working with Parent-Child Dimensions
- MSAS : Basics of Levels
- MSAS : Working with Standard Dimensions
- MSAS : Shared vs Private Dimensions
- Understanding Dimension Basics
- MSAS : Office 2000 OLAP Components
- MSAS : Client Architecture
- MSAS : Cube Storage options
- MSAS : Meta data Repository
- MSAS : Analysis services Tools for Extended Functionality
- MSAS : The Wizards
- MSAS : The Analysis Manager and Analysis Server
- MSAS : The Data warehousing framework of SQL Server 2000 - Part 2
- MSAS : The Data warehousing framework of SQL Server 2000 - Part 1
- MSAS : Microsoft Data Warehousing Overview
- MSAS : Browsing the Cube
- MSAS : Designing Storage and Processing the Cube
- MSAS : Building the Cube Part #3
- MSAS : Building the Cube Part #2
- MSAS : Building the Cube Part #1
- MSAS : Setting up the Database in Analysis Server
- MSAS : Preparing to Create the Cube
- MSAS : Introducing Analysis Manager Wizards
- Microsoft Analysis Services Installation
- MSAS - Applying OLAP Cubes
- Understanding OLAP Models
- Designing the Dimensional Model and Preparing the data for OLAP
- Design of the data warehouse: Kimball Vs Inmon
- Defining OLAP Solutions and Data Warehouse design
- Microsoft Analysis Services Training
- Data Warehouse database and OLTP database
- Introduction to Data Warehousing









