Building a Web-Based Analysis System
Part 1
A real-world look at using the Analysis Services Thin Web Client Browser
Mark Scott, John Lynn
Using OWC to Deploy Office on the Web
When working with analytical databases, analysts organize data into common groups and try to determine what would happen if things were different.
For example, would increasing a products price—which would increase profit per unit but probably reduce number of units sold—yield a higher or lower overall profit? Or how would a drop in the federal discount rate affect the yield of real estate loans? To help analysts make educated projections based on historical trends, Microsoft provides Analysis Services in SQL Server 2000 and OLAP Services in SQL Server 7.0. These services provide OLAP capability and can process data stored in SQL Server (or any other OLE DB—compatible data source) into multidimensional data structures called cubes. Data cubes simplify the process of analyzing trends and correlating the way entities interact with one another.
For example, real estate investors use cash-flow modeling to isolate a group of loans that have common characteristics (e.g., types of properties, geographic area, range of interest rates) and project the effects of different kinds of events. What will happen if loans mature more rapidly than expected or if the borrowers default? And how might such unpredictable events affect the yield of bonds that the loans secure?
Selecting from lists that can include hundreds of loans and isolating the loans that have the characteristic that youre analyzing can be tricky. Analysis Services and OLAP Services can help correlate these groups of loans so that analysts can model loan assumptions. To help a clients real estate analysts project the performance of commercial mortgage-backed securities, our development team needed to devise a system that simplified the grouping of loans in different ways—such as by their interest rate, term to maturity, or property location. The interface needed to be easy to learn and use. And the system we developed needed to be securely deployed through the Internet. To meet these criteria, the development team chose Analysis Services.
Having settled on a back-end technology, the development team began working on a plan for implementing the front-end interface. Most financial analysts use Microsoft Excel and are familiar and comfortable with its interface. Excel includes PivotTable Service, which lets analysts connect to Analysis Services databases. Excels drag-and-drop interface provides simple, intuitive access to multidimensional data without requiring users to have extensive training. And by using Excels graphing capabilities, users can present data in graphs and charts. So for the front-end interface, the teams first choice was Excel 2002, which is part of Microsoft Office XP. Figure 1 shows Excels PivotTable Service exploring an Analysis Services OLAP cube.
Excel would have been a fine choice—if all the clients users worked together in the same building and could access the Analysis server through the same LAN. But because the users needed to share the application from a variety of organizations whose offices are scattered around the world, the team needed a component similar to Excel that users could access through the Internet. The team found the solution to this challenge in Office Web Components. OWC is a set of ActiveX controls that you can use on Web pages to provide Office functionality. The OWC PivotTable component is a Web version of Excels PivotTable Service; PivotTable uses PivotTable Service and requires that PivotTable Service be installed before it will run. But the OWC PivotTable works without Excel.
PivotTable can retrieve multidimensional data from an Analysis server and present the data in an interactive, drag-and-drop interface. Users who have Microsoft Internet Explorer (IE) 4.01 or later can use OWC to analyze Analysis Services data without installing additional component software. Figure 2 shows the OWC PivotTable client interface, which looks and works like the familiar Excel interface. The OWC PivotTable also provides intelligent caching, which improves performance by reducing the number of trips PivotTable makes through the network to the server. So by actively working with Analysis Services, PivotTable can reduce data transfer and work faster.
Although OWC provided everything our development teams project needed, we encountered problems when we tried to deploy OWC across the Internet. The first problem was the platform that OWC runs on. The Office XP version of OWC requires Microsoft Data Access Components (MDAC) 2.6 or later. Many of the service subscribers use Windows NT Workstation 4.0 as their OS, and to install MDAC 2.6, they also had to install Service Pack 6 (SP6). One of the primary attractions of using OWC was that we thought deployment would be seamless. We discovered that although we could automate the process of installing service packs, the process requires reboots and is intrusive. Microsoft later provided a revised version of the OWC component that works with SP4, but at the time we were developing our application, the deployment of service packs in the tightly controlled client network of a financial institution was a significant barrier. Thus, a solution that required a specific service pack for the OS wasnt a viable option.
The second problem that our team encountered was connectivity. OWC requires a direct connection to the Analysis Services data source. OWC communicates directly with the Analysis server through the default port, 2725, which is a
剩余内容已隐藏，支付完成后下载完整资料
Building a Web-Based Analysis System
Part 1
A real-world look at using the Analysis Services Thin Web Client Browser
Mark Scott, John Lynn
Using OWC to Deploy Office on the Web
When working with analytical databases, analysts organize data into common groups and try to determine what would happen if things were different.
For example, would increasing a products price—which would increase profit per unit but probably reduce number of units sold—yield a higher or lower overall profit? Or how would a drop in the federal discount rate affect the yield of real estate loans? To help analysts make educated projections based on historical trends, Microsoft provides Analysis Services in SQL Server 2000 and OLAP Services in SQL Server 7.0. These services provide OLAP capability and can process data stored in SQL Server (or any other OLE DB—compatible data source) into multidimensional data structures called cubes. Data cubes simplify the process of analyzing trends and correlating the way entities interact with one another.
For example, real estate investors use cash-flow modeling to isolate a group of loans that have common characteristics (e.g., types of properties, geographic area, range of interest rates) and project the effects of different kinds of events. What will happen if loans mature more rapidly than expected or if the borrowers default? And how might such unpredictable events affect the yield of bonds that the loans secure?
Selecting from lists that can include hundreds of loans and isolating the loans that have the characteristic that youre analyzing can be tricky. Analysis Services and OLAP Services can help correlate these groups of loans so that analysts can model loan assumptions. To help a clients real estate analysts project the performance of commercial mortgage-backed securities, our development team needed to devise a system that simplified the grouping of loans in different ways—such as by their interest rate, term to maturity, or property location. The interface needed to be easy to learn and use. And the system we developed needed to be securely deployed through the Internet. To meet these criteria, the development team chose Analysis Services.
Having settled on a back-end technology, the development team began working on a plan for implementing the front-end interface. Most financial analysts use Microsoft Excel and are familiar and comfortable with its interface. Excel includes PivotTable Service, which lets analysts connect to Analysis Services databases. Excels drag-and-drop interface provides simple, intuitive access to multidimensional data without requiring users to have extensive training. And by using Excels graphing capabilities, users can present data in graphs and charts. So for the front-end interface, the teams first choice was Excel 2002, which is part of Microsoft Office XP. Figure 1 shows Excels PivotTable Service exploring an Analysis Services OLAP cube.
Excel would have been a fine choice—if all the clients users worked together in the same building and could access the Analysis server through the same LAN. But because the users needed to share the application from a variety of organizations whose offices are scattered around the world, the team needed a component similar to Excel that users could access through the Internet. The team found the solution to this challenge in Office Web Components. OWC is a set of ActiveX controls that you can use on Web pages to provide Office functionality. The OWC PivotTable component is a Web version of Excels PivotTable Service; PivotTable uses PivotTable Service and requires that PivotTable Service be installed before it will run. But the OWC PivotTable works without Excel.
PivotTable can retrieve multidimensional data from an Analysis server and present the data in an interactive, drag-and-drop interface. Users who have Microsoft Internet Explorer (IE) 4.01 or later can use OWC to analyze Analysis Services data without installing additional component software. Figure 2 shows the OWC PivotTable client interface, which looks and works like the familiar Excel interface. The OWC PivotTable also provides intelligent caching, which improves performance by reducing the number of trips PivotTable makes through the network to the server. So by actively working with Analysis Services, PivotTable can reduce data transfer and work faster.
Although OWC provided everything our development teams project needed, we encountered problems when we tried to deploy OWC across the Internet. The first problem was the platform that OWC runs on. The Office XP version of OWC requires Microsoft Data Access Components (MDAC) 2.6 or later. Many of the service subscribers use Windows NT Workstation 4.0 as their OS, and to install MDAC 2.6, they also had to install Service Pack 6 (SP6). One of the primary attractions of using OWC was that we thought deployment would be seamless. We discovered that although we could automate the process of installing service packs, the process requires reboots and is intrusive. Microsoft later provided a revised version of the OWC component that works with SP4, but at the time we were developing our application, the deployment of service packs in the tightly controlled client network of a financial institution was a significant barrier. Thus, a solution that required a specific service pack for the OS wasnt a viable option.
The second problem that our team encountered was connectivity. OWC requires a direct connection to the Analysis Services data source. OWC communicates directly with the Analysis server through the default port, 2725, which is a
剩余内容已隐藏，支付完成后下载完整资料
资料编号：[500051]，资料为PDF文档或Word文档，PDF文档可免费转换为Word
以上是毕业论文外文翻译，课题毕业论文、任务书、文献综述、开题报告、程序设计、图纸设计等资料可联系客服协助查找。
.gif){kind=link}
.gif){kind=link}