There are several levels at which you can work with analytic workspaces:
Installation of the OLAP option with the Oracle Database includes the following components:
The following applications can provide important functionality when working in OLAP, and are available online at the Oracle Web site:
All of these components and applications are described in the following paragraphs. The relationships among them are described throughout this guide.
OLAP Analytic Engine
The OLAP analytic engine supports the selection and rapid calculation of multi dimensional data. The status of an individual session persists to support a series of queries, which is typical of analytical applications; the output from one query is easily used as input to the next query. A comprehensive set of data manipulation tools supports modeling, aggregation, allocation, forecasting, and what-if analysis. The OLAP engine runs within the Oracle kernel.
Analytic workspaces store data in a multidimensional format where it can be manipulated by the OLAP engine. An analytic workspace is stored as a LOB table in a relational schema. Within a single database, many analytic workspaces can be created and shared among users. Like a relational schema, an analytic workspace is owned by a particular user ID, and other users can be granted access to it. Because individual users can save a personal copy of their alterations to a workspace, the workspace environment is particularly conducive to planning applications.
Analytic Workspace Manager
Analytic Workspace Manager provides a user interface for creating an analytic workspace in database standard form. This form enables the analytic workspace to be used with various tools that aggregate, refresh, and enable the data so that it is accessible to OLAP applications. These tools are also provided by Analytic Workspace Manager.
OLAP Worksheet is an interactive environment for working with analytic workspaces, similar to SQL*Plus Worksheet. It provides easy access to the OLAP DML, and enables you to perform sophisticated business analysis, such as modeling, forecasting, and allocation. You can switch between two different modes, one for working with analytic workspaces in the OLAP DML, and the other for working with relational tables and views in SQL. It is available through Analytic Workspace Manager or as a separate executable.
SQL Interface to OLAP
The SQL interface to OLAP provides access to analytic workspaces from SQL. The SQL interface is implemented in PL/SQL packages. These are the primary ones:
OLAP DML is a mature low-level language that is native to analytic workspaces. It is the data definition and manipulation language for creating analytic workspaces, defining data containers, and manipulating the data stored in these containers. All other levels of operation (GUIs, Java, and SQL) resolve to the OLAP DML. It offers the maximum power and flexibility in acquiring, manipulating, and analyzing data. If you are upgrading from Oracle Express, or if your data is stored in formats not supported by the higher level tools, then you may work directly in the OLAP DML at an early stage. Otherwise, you may use the OLAP DML directly only to enhance the functionality of your workspaces.
OLAP Catalog is the metadata repository provided for the OLAP option. It consists of write APIs, which are a set of PL/SQL procedures, and read APIs, which are relational views within the Oracle Database. The metadata describes data, which is presented as a star schema, in multidimensional terms such as cubes, measures, dimensions, and attributes. The OLAP Catalog is used to perform two distinct functions:
The OLAP Catalog read APIs make the metadata that you have defined available to applications. They are useful to any application that uses SQL SELECT statements to run against views of analytic workspace data. SQL applications do not require the use of the OLAP Catalog, but may benefit from using it. They can run against the logical objects that are defined in the OLAP catalog, without an awareness of where the underlying data resides.
Analytic Workspace Java APIs
The Analytic Workspace Java APIs provide a Java interface for the creation and maintenance of analytic workspaces. These APIs are an alternative to using the OLAP Catalog for defining an analytic workspace build.
The OLAP API is the Java-based programming interface for OLAP applications, and supports the BI Beans. The BI Beans are building blocks for developing analytic applications in Java, and are available for use with JDeveloper. If you are a Java developer, then you should consider using the BI Beans for your analytic applications. Note that the BI Beans are not included with the OLAP option, but they require an OLAP-enabled Oracle Database.
Oracle Enterprise Manager
Oracle Enterprise Manager is a system management tool that provides you with an integrated solution for managing Oracle products without formulating complex SQL commands. You can use Enterprise Manager to set up user accounts, define tablespaces, monitor performance, and do other administrative tasks associated with your database, including the OLAP option.
The OLAP Management tool is part of the Enterprise Manager support for data warehouses. Using a graphical user interface, you can define logical metadata dimensions, measures, and cubes in the OLAP Catalog for the dimension tables and fact tables of a star or snowflake schema that complies with the database requirements for creating a dimension.
Oracle Warehouse Builder
Oracle Warehouse Builder can extract data from many different sources, transform it into a star schema in the relational database, generate OLAP Catalog metadata, and create an analytic workspace. Warehouse Builder provides an alternative to using the OLAP Management tool in Enterprise Manager, and the Create Analytic Workspace wizard in Analytic Workspace Manager. The resulting analytic workspace is in database standard form, so you can then use Analytic Workspace Manager to aggregate, enhance, and enable your data. If your data requires transformation, then Oracle Warehouse Builder provides the best method for generating an analytic workspace. Once you have created a logical model for your data warehouse, Oracle Warehouse Builder requires only a few extra steps to generate an analytic workspace in addition to a star schema.
OLAP Related Interview Questions
|Informatica Interview Questions||Data Warehouse ETL Toolkit Interview Questions|
|PL/SQL Interview Questions||Data Warehousing Interview Questions|
|Testing Tools Interview Questions||SQL Database Interview Questions|
|MySQL Interview Questions||ERP Tools Interview Questions|
|Oracle 11g Interview Questions||Hyperion Financial Management Interview Questions|
|Hyperion Essbase 5 Interview Questions||Database Design Interview Questions|
|Data modeling Interview Questions||Oracle Hyperion Planning Interview Questions|
|Biztalk Esb Toolkit Interview Questions|
OLAP Related Practice Tests
|Informatica Practice Tests||PL/SQL Practice Tests|
|Data Warehousing Practice Tests||Testing Tools Practice Tests|
|SQL Database Practice Tests||MySQL Practice Tests|
|ERP Tools Practice Tests||Oracle 11g Practice Tests|
|Hyperion Financial Management Practice Tests||Hyperion Essbase 5 Practice Tests|
|Database Design Practice Tests|
The Multidimensional Data Model
The Sample Schema
Developing Java Applications For Olap
Defining A Logical Multidimensional Model
Creating An Analytic Workspace
Sql Access To Analytic Workspaces
Exploring A Standard Form Analytic Workspace
Adding Measures To A Standard Form Analytic Workspace
Predicting Future Performance
Acquiring Data From Other Sources
Administering Oracle Olap
Materialized Views For The Olap Api
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