Oracle Portal Oracle Application Server Tips by Burleson Consulting

The component allows for the fast definition and deployment of web pages.  Like the non-Oracle tools such as DreamWeaver and MS FrontPage, Oracle Portal allows the developer to create and deploy web content.  The important difference is that Oracle Portal allows the developer to include content dynamically created, personalized web pages from multiple data sources using Portlets.  The Oracle Portal product provides the following features:

• Portal page creation, management and maintenance.

• The assembly of web content from multiple sources using Portlets.

• Web page content that contains data retrieved from a database.

• Portal content publishing facilities using easy wizards.

• Advanced features such as text searching (via Oracle Text) and wireless support via XML and HTML  interfaces

These components fit-together into an architecture that allows developers to quickly create and deploy web page content (Figure 1.8).

Figure 8: The Oracle9iAS Portal Architecture

In Figure 1.8 we see that Portal administrator defining the Portlet content and the content for the basic web pages.  At run-time, Portal users access these definitions to create dynamic publishing content, using the Portlet definitions, the web page definitions, and data from inside the Oracle database. It is beyond the scope of this book to examine all of the content deliver features of Oracle Portal.  For complete information of using Oracle Portal see the Oracle Press book Oracle9i Application Server Portal Handbook by Vandiver & Cox.

Oracle Discoverer

This component allows for the easy end-user query implementation. In essence, Oracle Discoverer is an ad-hoc query, reporting, analysis, and Web publishing tool. Like Crystal Reports and Business Objects, Oracle Discoverer provides a GUI metaphor for the specification of Oracle database content and display format. 

In addition Oracle Discoverer is a business analysis intelligence tools, with interfaces with Oracle Clickstream and the Oracle database.  When using Oracle Discoverer, the end-user develops workbooks.  At a high level, a workbook is a bundle of metadata that includes the following components:

• The tables that participate in the query

• The report formatting for the result set

• The calculations to perform on the data

Once defined, these workbooks allow inexperienced end-users to easily create ad-hoc reports against the Oracle database using the Discoverer End-User Layer (EUL) GUI interface.  In addition, Oracle Discoverer allows for the end user to view summary data at several levels, and includes components that allow the end-user to drill-down into more detail or roll-up into summary level (Figure 1.9).

Figure 9: Oracle9iAS Discoverer Architecture

As we see in Figure 1.9, there are two main phases in Discoverer usage.  The first step is the Discoverer Administrator creating the workbooks by specifying the tables, formatting and computation rules for any given report.  The second phase is the run-time phase, where the end-user accesses the EUL and created customized reports using the Discoverer Wizards.

The core of administration for Oracle Discoverer is the development and maintenance of the workbooks and metadata objects.  For example, each time and end-user runs a report, Discoverer refers to eul_qpp_statistics metadata table in the infrastructure to produce a time estimate for the report.  For more details on the administration and use of Oracle Discoverer, see the Oracle Press book, Oracle Discoverer Handbook, Armstrong-Smith.

Oracle Form Server

This component is used to format and deploy and render end-user presentation pages.  An evolution of the Oracle SQL*Forms application development tool, the Oracle Forms Server was originally used to render screen display from Oracle content.  Enhanced to provide support for HTML, Oracle Forms Server is now used within Oracle9iAS to render web pages that include Oracle database content.

Because the Oracle Forms Server is the main engine for rendering web pages, the tuning and administration of the Forms Server is a critical aspect of Oracle9iAS administration.  We will be discussing Oracle Forms Server administration and tuning in more details in Chapter 10, Performance Tuning with Oracle9iAS.

Oracle Personalization

Analyzing page viewing behavior and creating custom web page content on a busy eCommerce site is a formidable computing challenge. To address these issues, Oracle has developed the Oracle9iAS personalization and the Oracle data mining suite. Oracle personalization is extremely sophisticated and relies on internal data about end-users web-page visits, web-page clicks, and referrer statistics.  Even more powerful, Oracle personalization allows for the incorporation of external metadata such as customer demographics.  It is worthwhile to note that Oracle has several competitors in the web personalization market, notably Blue Martini, Vignette and Personify.

The goal of Oracle9iAS personalization is to accurately identify classes of end-users and correlate their behavior with the behavior of other known groups of end-users.  Using sophisticated multivariate correlation techniques; web-page contact can be customized according to predictions about each end-users preference for web page content.  The nature of this analysis is very resource intensive, and almost all large Oracle9iAS shops devote large servers exclusively for developing these predictive recommendations.

IT marketing professionals know that it is critical of get the right products onto a custom web page. To be successful, Oracle9iAS must be able to accurately predict your propensity to buy a product, based on prior buying and browsing patterns, and buying patterns of like-minded customers (customer profiling).  The challenge in developing these predictive models is accurately placing visitors into consumer groups. A consumer group is a group of customers with similar demographics and buying patterns.

Figure 1.10 shows the process of analyzing demographic information to place visitors into consumer groups. A visitor can be placed into a consumer group in two ways:

• Their demographic category (collected from personal information)

• Their pattern of page views (collected from referrer URLs)

Figure 10: Architecture of Oracle personalization

Once we have defined consumer groups in Oracle Personalization, we next start a data mining procedure to correlate the patterns of each consumer group to specific products. The customized HTML personalization is based on data from three sources:

• Known consumer group data ? These groups consist of predetermined summaries of consumer group characteristics.

• Weighted rankings of pages viewed ? This is a measure of the popularity of product pages according to each consumer group.

• Historical data ? This is historical sales data, correlated by consumer group.

Oracle Personalization uses these sophisticated consumer group and data mining component mechanisms to create the web content (Figure 1.11).  The administration of Oracle Personalization is simplified by using the Oracle Personalization GUI, and the Oracle documentation has an excellent discussion of Oracle9iAS Personalization administration.

Figure 11: The Oracle9iAS Personalization Engine at runtime

This is an excerpt from "Oracle 10g Application Server Administration Handbook" by Don Burleson and John Garmany.