Introducing Oracle OLAP option to Oracle Database 11g

Oracle OLAP (Online Analytical Processing) is a multidimensional analytic engine that is implanted in Oracle Database11g. It is used to do complicated calculations using simple SQL queries with extremely fast response times. Because it is embedded in Oracle11g, it facilitates centralized management of data in a secure, manageable and scalable platform. It provides a means for hundreds of analytic functions to be combined in custom functions and to produce analytic measures, financial models, forecasts, regressions etc.

Oracle OLAP 11g contributes data warehouse features to Oracle Database 11g with increased performance. User’s queries are often varying and volatile. With standard relational systems it is complicated to optimize data structures to provide consistent high performance for changing query pattern. To address this need, usually application designers create views of summary data from tables or materialized views.


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However OLAP cubes is a data structure that allows and has the capability to manipulate and analyze data from multiple perspectives. It composes of numeric facts denoted as measures which are categorized by dimensions. They can be considered as extensions to a two dimensional array. The dimensions can be a simple list or structured into levels and hierarchies. Thus, an analyst can comprehend underlying data using multi-dimensional analysis.

The cube organized materialized views present in Oracle OLAP 11g enable cubes to provide an improved alternative to summary management. In this, when an application queries the database by using aggregate functions the query rewrite feature of the database re-directs the query to the cube organized materialized view which manages the summary data visibly to the query application and also provides improved query performance. Cube organized materialized views by default inherit the query and performance benefits of the cube inclusive of compressed cube aggregation technology, cost based aggregation, management of all feasible summaries in a single database object, array based storage and fast cell access and fast incremental refresh and aggregation.

Oracle OLAP stores data in the database in the form of multidimensional cubes that are organized for rapid incremental update and query. Hierarchical dimensions permit data to be consolidated from lower levels of summarization to higher levels. They provide support to drill-down navigation, time-series calculations and specific types of calculations like Share to Parent, Share within Ancestor etc. These calculations can be defined effortlessly within the analytic workspace manager which is the administrative tool of Oracle OLAP 11g. These are competently computed within the cube at runtime.

As the OLAP option executes within the Oracle Database instance there are no separate servers, users, or database files to deal with. The security and high availability features of Oracle are innate within it. The SQL interface to OLAP cubes enables any application that queries a star schema to easily query and benefit from its exemplary performance and analytic content.

In short, the architecture of Oracle database facilitates a single OLAP cube to play three different roles at the same time for business intelligence applications. They are either as a summary management solution or as a calculation engine to SQL based intelligence applications or also as a rich featured multi dimensional server, serving dimensionally oriented business intelligence applications.



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| An Introduction to Oracle’s JD Edwards EnterpriseOne Tools | Avoiding-sql-injection-in-pl-sql-oracle1og | Developing PL/SQL Web Applications in Oracle10g: An Overview | Identifying Rows by Address in Oracle 10g | Introducing Oracle OLAP option to Oracle Database 11g | Some Exciting New Features of Oracle11g | The Benefits of Partition for Improved Performance in Oracle Database 11g | Understanding Automatic SQL Tuning in Oracle10g | Using XMLTextReader Class for Better Access to XML |

 

 

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