Using Oracle R Enterprise to prepare and analyze data in an Oracle Database instance has many advantages for an R user. With Oracle R Enterprise, you can do the following:
Operate on Database-Resident Data Without Using SQL. Oracle R Enterprise has overloaded open source R methods and functions that transparently convert standard R syntax into SQL. These methods and functions are in packages that implement the Oracle R Enterprise transparency layer. With these functions and methods, you can create R objects that access, analyze, and manipulate data that resides in the database. The database can automatically optimize the SQL to improve the efficiency of the query.
Eliminate Data Movement. By keeping the data in the database, you eliminate the time involved in transferring the data to your desktop computer and the need to store the data locally. You also eliminate the need to manage the locally stored data, which includes tasks such as distributing the data files to the appropriate locations, synchronizing the data with changes that are made in the production database, and so on.
Keep Data Secure. By keeping the data in the database, you have the security, scalability, reliability, and backup features of Oracle Database for managing the data.
Use the Power of the Database. By operating directly on database-resident data, you can use the memory and processing power of the database and avoid the memory constraints of your client R session.
Use Current Data. As data is refreshed in the database, you have immediate access to current data.
Prepare Data in the Database. Using the transparency layer functions, prepare large database-resident data sets for predictive analysis through operations such as ordering, aggregating, filtering, recoding, and the use of comprehensive sampling techniques without having to write SQL code.
Save R Objects in the Database. You can save R objects in an Oracle Database instance as persistent database objects that are available to others. You can store R and Oracle R Enterprise objects in an Oracle R Enterprise datastore, which is managed by the Oracle database.
Build Models in the Database. You can build models in the database and store and manage them in an Oracle R Enterprise datastore. You can use functions in packages that you download from CRAN (The Comprehensive R Archive Network) to build models that require large amounts of memory and that use techniques such as ensemble modeling.
Score Data in the Database. You can include your R models in scripts to score database-resident data. You can perform tasks such as the following:
Go from model building to scoring in one step because you can use the same R code for scoring. You do not need to translate the scoring logic as required by some standalone analytic servers.
Schedule scripts to be run automatically to perform tasks such as bulk scoring.
Score data in the context of a transaction.
Perform online what-if scoring.
Optionally convert a model to SQL, which Oracle Database does automatically for you. You can then deploy the resulting SQL for low-latency scoring tasks.
Execute R Scripts in the Database. Using Oracle R Enterprise embedded R execution functionality, you can create, store, and execute R scripts in the database. When the script executes, Oracle Database starts, controls, and manages one or more R engines that can run in parallel on the database server. By executing scripts on the database server, you can take advantage of scalability and performance of the server.
With the embedded R execution functionality, you can do the following:
Develop and test R scripts interactively and make the scripts available for use by SQL applications
Use CRAN and other packages in R scripts on the database server
Operationalize entire R scripts in production applications and eliminate porting R code; avoid reinventing code to integrate R results into existing applications
Seamlessly leverage Oracle Database as a high performance computing (HPC) environment for R scripts, providing data parallelism and resource management
Use the processing and memory resources of Oracle Database and the increased efficiency of read/write operations between the database and the embedded R execution R engines
Use the parallel processing capabilities of the database for data-parallel or task-parallel operations
Perform parallel simulations
Generate XML and PNG images that can be used by R or SQL applications
Integrate with the Oracle Technology Stack. You can take advantage of all aspects of the Oracle technology stack to integrate your data analysis within a larger framework for business intelligence or scientific inquiry. For example, you can integrate the results of your Oracle R Enterprise analysis into Oracle Business Intelligence Enterprise Edition (OBIEE).