Building Scalable Analysis Services Applications - Microsoft SQL Server 2008 Analysis Services - page 447

CHAPTER 25

IN THIS CHAPTER

. Approaches to Scalability

Building Scalable
Analysis Services
Applications

. OLAP Farm

. Linked Dimensions and

Measure Groups

. Remote Partitions

. Using Business Intelligence

Development Studio to Create
Linked Dimensions

A nalysis Services supports multiple functionalities that
increase the scalability and flexibility of your system by
distributing data among servers. A distributed data system
helps you to better:

. Shared Scalable Databases

. Attach, Detach, Read-Only, and

DbStorageLocation

. Increase the number of users that can simultaneously

use the server

. Increase the volume of data stored in the system

. Extend the data model by including dimensions and

measure groups from external models

Approaches to Scalability

You can approach scalability from two directions: scale up
or scale out. With a scale-up approach, you increase the
processing power of a single computer. With a scale-out
approach, you increase the number of computers that
contain your data. Both approaches have pros and cons. In
the following sections, we look at these approaches to scala-
bility from the perspective of Analysis Services.

The Scale-Up Approach

To scale your system, you add more processing power to a
single physical computer or you transfer your application to
another, more powerful computer. To scale data volumes,
you add additional space to your hardware storage or
increase the speed of storing data. The following lists
describe in more detail the advantages of a scale-up solu-
tion.