Oracle OLAP provides the query performance and calculation capability previously found only in multidimensional databases to Oracle's relational platform. In addition, it provides a Java OLAP API that is appropriate for the development of internet-ready analytical applications. Unlike other combinations of OLAP and RDBMS technology, Oracle OLAP is not a multidimensional database using bridges to move data from the relational data store to a multidimensional data store. Instead, it is truly an OLAP-enabled relational database. As a result, Oracle provides the benefits of a multidimensional database along with the scalability, accessibility, security, manageability, and high availability of the Oracle database. The Java OLAP API, which is specifically designed for internet-based analytical applications, offers productive data access.
Another resource management facility is the progress monitor, which gives end users and administrators the status of long-running operations. Oracle maintains statistics describing the percent-complete of these operations. Oracle Enterprise Manager lets you view a bar-graph display of these operations showing what percent complete they are. Moreover, any other tool or any database administrator can also retrieve progress information directly from the Oracle data server using system views.
Benefits of OLAP and RDBMS Integration
Basing an OLAP system directly on the Oracle database server offers the following benefits:Scalability
There is tremendous growth along three dimensions of analytic applications: number of users, size of data, and complexity of analyses. There are more users of analytical applications, and they need access to more data to perform more sophisticated analysis and target marketing. For example, a telephone company might want a customer dimension to include detail such as all telephone numbers as part of an application that is used to analyze customer turnover. This would require support for multi-million row dimension tables and very large volumes of fact data. Oracle can handle very large data sets using parallel execution and partitioning, as well as offering support for advanced hardware and clustering.Availability
Partitioning allows management of precise subsets of tables and indexes, so that management operations affect only small pieces of these data structures. By partitioning tables and indexes, data management processing time is reduced, thus minimizing the time data is unavailable. Transportable tablespaces also support high availability. With transportable tablespaces, large data sets, including tables and indexes, can be added with almost no processing to other databases. This enables extremely rapid data loading and updates.Manageability
Oracle lets you precisely control resource utilization. The Database Resource Manager, for example, provides a mechanism for allocating the resources of a data warehouse among different sets of end-users.Another resource management facility is the progress monitor, which gives end users and administrators the status of long-running operations. Oracle maintains statistics describing the percent-complete of these operations. Oracle Enterprise Manager lets you view a bar-graph display of these operations showing what percent complete they are. Moreover, any other tool or any database administrator can also retrieve progress information directly from the Oracle data server using system views.
Backup and Recovery
Oracle provides a server-managed infrastructure for backup, restore, and recovery tasks that enables simpler, safer operations at terabyte scale. Some of the highlights are:- Details related to backup, restore, and recovery operations are maintained by the server in a recovery catalog and automatically used as part of these operations.
- Backup and recovery operations are fully integrated with partitioning. Individual partitions, when placed in their own tablespaces, can be backed up and restored independently of the other partitions of a table.
- Oracle includes support for incremental backup and recovery using Recovery Manager, enabling operations to be completed efficiently within times proportional to the amount of changes, rather than the overall size of the database.
Security
The security features in Oracle have reached the highest levels of U.S. government certification for database trustworthiness. Oracle's fine grained access control enables cell-level security for OLAP users. Fine grained access control works with minimal burden on query processing, and it enables efficient centralized security management.
Overview of Data Mining
Oracle Data Mining (ODM) embeds data mining within the Oracle Database. The data never leaves the database — the data, data preparation, model building, and model scoring results all remain in the database. This enables Oracle to provide an infrastructure for application developers to integrate data mining seamlessly with database applications. Some typical examples of the applications that data mining are used in are call centers, ATMs, ERM, and business planning applications.
By eliminating the need for extracting data into specialized tools and then importing the results back into the database, you can save significant amounts of time. In addition, by having the data and the data model in the same location (an Oracle database), there is no need to export the model as code.
Data mining functions such as model building, testing, and scoring are provided through a Java API.
Oracle Data Mining supports the following algorithms:
- For classification, Naive Bayes, Adaptive Bayes Networks, and Support Vector Machines (SVM)
- For regression, Support Vector Machines
- For clustering, k-means and O-Cluster
- For feature extraction, Non-Negative Matrix Factorization (NMF)
- For sequence matching and annotation, BLAST
SOURCE:http://www.stanford.edu/dept/itss/docs/oracle/10g/server.101/b10743/bus_intl.htm
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