Читать книгу Applied Microsoft Business Intelligence - Sarka Dejan - Страница 18

As mentioned earlier, performance is often a driving factor behind a large percentage of business intelligence projects. Most of the time this performance is related to accessing data and producing reports. While some may argue, including myself, that a business intelligence project should solve a problem, ultimately the end goal must be granting end users access to data in an effective but also efficient way. Satisfying this goal is accomplished by architecting a server topology that can scale and grow. This is where the Microsoft business intelligence stack lends itself perfectly. Figure 2.4 illustrates a sample SharePoint deployment.

Figure 2.4 Sample Microsoft business intelligence server topology

This configuration is scaled out to support a high number of end users and a growing number of requests. You could reduce the number of servers in this configuration by consolidating the web server and application server, but this could adversely affect performance depending on the number of requests sent to the web server. Therefore, as a best practice, always separate the two in anticipation of some type of growth. In addition, as the end-user base grows, SharePoint provides the flexibility of adding more web and application servers to accommodate the increasing population. With multiple servers in place, not only has scale been introduced, but now SharePoint can use its internal load-balancing features to provide optimal performance for end users.