|Oracle9i OLAP Developer's Guide to the OLAP API
Release 2 (9.2)
Part Number A95297-01
Introduction to the OLAP API, 2 of 6
The OLAP API is a Java application programming interface (API) through which an application can access data for online analytical processing (OLAP). It is the API that is supplied with Oracle OLAP, an Oracle component.
The purpose of the OLAP API is to facilitate the development of OLAP applications, which allow users to dynamically select, aggregate, calculate, and perform other analytical tasks on data through a graphical user interface. Typically, the user interface of an OLAP application displays data in multidimensional formats, such as graphs and crosstabs.
In general, OLAP applications are developed within the context of business intelligence and data warehousing systems, and the features of the OLAP API are optimized for this type of application. With the OLAP API, a Java application can access, manipulate, and display data in multidimensional terms. The OLAP API also makes it possible to define a query in a step-by-step process that allows for undoing individual query steps without recreating the entire query. Such multistep queries are easy to modify and refine dynamically.
Data warehousing and OLAP applications are based on a multidimensional view of data, and they work with queries that represent selections of data. The following definitions introduce concepts that reflect the multidimensional view and are basic to data warehousing, OLAP, and the OLAP API:
Two additional data warehouse and OLAP concepts, cube and edge, are not intrinsic to the OLAP API, but are often incorporated into the design of applications that use the OLAP API.
For more information about all of these concepts, see the Oracle Data Warehousing Guide.
The OLAP API, as part of Oracle OLAP, makes it possible for Java applications (including applets) to access data that resides in an Oracle data warehouse. A data warehouse is a relational database that is designed for query and analysis, rather than transaction processing. Warehouse data often conforms to a star schema, which represents a multidimensional data model. The star schema consists of one or more fact tables and one or more dimension tables that are related through foreign keys. Typically, a data warehouse is created from a transaction processing database by an extraction transformation transport (ETT) tool, such as Oracle Warehouse Builder.
In order for the OLAP API to access the data in a given data warehouse, a database administrator must first ensure that the data warehouse is configured according to an organization that is supported by Oracle OLAP. The star schema is one such organization, but not the only one. Once the data is organized in the warehouse, the database administrator must use the OLAP Metadata APIs to create the required metadata, which can be defined as "data about the data." Finally, with the metadata in place, an application can access both the data and the metadata through the OLAP API.
See the Oracle9i OLAP User's Guide for information about supported data warehouse configurations and about using the OLAP Metadata APIs.
The collection of warehouse data for which a database administrator has created metadata using the OLAP metadata API is referred to as the data store to which the OLAP API gives access. Of course, each user who accesses data through the OLAP API might have security restrictions that limit the scope of the data that he or she can access within the data store.
Through the OLAP API, an application can do the following:
The OLAP API is a Java API, so it has all the advantages of the Java environment. It is platform independent, and it provides the benefits of an object-oriented API, such as abstraction, encapsulation, polymorphism, and inheritance. These strengths are built into the OLAP API, and because the client application is written in Java, its code can also take advantage of them.
In order to work with the OLAP API, application developers should have familiarity with Java, object-oriented programming, relational databases, data warehousing, and multidimensional OLAP concepts.