Oracle olap what is

Just to complicate matters, analytic workspaces are themselves stored within LOBs in Oracle relational tables, but the way they are created and maintained is quite different to data in relational tables. All of this additional work is carried out for you automatically, when you use the Oracle Enterprise Manager GUI to create your dimension, or you can enter the commands manually, as listed above.

Cube objects are one or more measures, that are dimensioned by by a common set of dimension objects. To create a simple cube that has one measure and uses our one dimension, first of all create a table to contain the measure. As an alternative to storing dimensions and measures in relational tables, we can also store them in analytic workspaces. Analytic Workspaces are multidimensional workspaces held within LOBs in Oracle tables, that store data using a technology originally introduced with Oracle's Express line of products.

Oracle Express was originally a product designed and sold by a company called IRI, who sold the technology to Oracle in who then rebadged it and sold it as a specialist OLAP server product for high-end analysis. Eventually, Oracle took this technology and incorporated it into Oracle 9i, and you can now store your OLAP data in these Express-derived analytic workspaces if your application requires high-end analysis, forecasting, analysis or OLAP calculations.

Because the OLAP Option is based on the Express Server calculation engine and multidimensional datatypes, it brings across all the Express functionality such as forecasts and demand plans, support for financial models, allocations and budgeting, and support for what-if analysis.

Also, unlike relational OLAP cubes, multidimensional OLAP Option cubes are usually "fully solved," with all aggregations computed at load time, giving a faster, more predictable response time for users' queries.

The first step in working with multidimensional datatypes is to create an analytic workspace. To create your first analytic workspace, type in. Your analytic workspace should now be created. Next, we need to create some dimensions.

In our case we want to create two dimensions, a new one called "Geography" and one called "Product. Note however that these two product dimensions are completely separate and have no relation between each other. For example, with our Geography dimension, we'd type in. The key differences between OLAP Option dimensions and relational dimensions are that relational dimensions use level-based dimensions, whilst OLAP Option dimensions are parent-child based.

Level-based Dimensions' hierarchies are defined by the relationship between levels, and levels map to columns in relational tables. The values that are to be contained in the dimensions are loaded in a later process, together with the links between dimension members that are loaded into the relation object. Now, do the same for our products dimension. Express Server is end of life now but still used by many organisations around the world but was a market leading standalone multidimensional database, acquired by Oracle in , and subsequently integrated into the Oracle Database.

It combines first class multidimensional data types, and calculation engine with the other performance, scalability, security, high availability and manageability features of Oracle Database. More usually, Analytic Workspaces and their multidimensional objects - dimensions, hierarchies, measures and calculations etc - are created, populated, refreshed and maintained by one or more of the tools that Oracle provides:.

Oracle Database OLAP cubes deliver excellent query performance, which scales well for large numbers of concurrent users. Oracle Database OLAP Option's cubes are full-blown multidimensional structures and support calculations that are difficult, complex, or even impossible to define using standard SQL. Other, standalone multidimensional databases on the market require specialized multidimensional query languages to access their data and leverage their calculation engines.

Most are proprietary, though in recent years a Microsoft language called MDX MultiDimensional eXpressions has become popular although each vendor has ended up coding to different versions of MDX as there is no published standard for it. This is a significant development. Even what would otherwise be very complex calculations such as time series calculations, aggregations with mixed or non additive aggregation methods, allocations, forecasts etc show up to the SQL query layer as if they are fully solved columns that can simply be SELECTed in SQL.

Even if the calculations are being performed on the fly by the Oracle Database in OLAP Cubes as is usually the case , the SQL used can 'assume' that all the measures and calculated measures have already been aggregated or allocated, or forecasted and calculated. Because the SQL required is so simple, developing and testing custom calculation-intensive applications is also dramatically simplified.

The amount of code, and its complexity will be much less than if the same thing is attempted without OLAP. As of Database 11g, the only 'special' requirement is that the tool or application has some basic 'aggregate awareness' or can be configured that way.

Regular relational table based MVs have been available in Oracle Database since Oracle 8, and are widely used by BI systems as they simplify the summary management aspects of those systems, and also deliver a feature called query re-write which can improve query performance.

You can define a connection to each database that you use for OLAP. After you define a connection, the database instance is listed in the navigation tree for you to access at any time. Right-click the top Databases folder in the navigation tree, then choose New Database Connection from the shortcut menu. Figure shows the connection information on the General tab of the New Database Connection dialog box. Plugins extend the functionality of Analytic Workspace Manager.

Plugins are distributed as JAR files. Any Java developer can create a plugin. The developer should provide information about what the plugin does and how to use it. If you have one or more plugins, then you must identify their location to Analytic Workspace Manager. Select Enable Plugins and identify the plugin directory. Click OK. The original analytic workspace remains accessible and unchanged by the upgrade process.

The original relational source data must be available to load into the new analytic workspace. If the data is in a different schema or the table names are different, then you must remap the dimensional objects to the new relational sources after the upgrade. However, if you choose to create the OLAP 11 g analytic workspace in a different schema, you must grant the new user the appropriate privileges as described in "Granting Privileges to DBAs and Application Developers".

To upgrade an OLAP 10 g analytic workspace:. If necessary, create a new database connection to the database instance with the analytic workspace. See "Defining a Database Connection". Open the database connection. See "Opening a Database Connection". Right-click the analytic workspace and select Create 11g Upgrade Template for 10g Analytic Workspace.

Save the XML template to a file. The Create 11g Upgrade Template for 10g Analytic Workspace dialog box is displayed if any subobjects, such as a level and a hierarchy, have the same name.