1.5 Typical Operations in Using Oracle R Enterprise

In using Oracle R Enterprise, the following is a typical progression of operations:

In an R session, connect to a schema in an Oracle Database instance.
Attach the schema and synchronize with the schema objects, which generates Oracle R Enterprise proxy objects for database tables.
Prepare the data for analysis and possibly perform exploratory data analysis and data visualization.
Build models using functions in the OREmodels or OREdm packages.
Score data using the models either in your local R session or by using embedded R execution.
Deploy the results of the analysis to end users.

Figure 1-1 Typical Oracle R Enterprise Workflow

This figure illustrates these steps and typical reiterations of them.

Description of "Figure 1-1 Typical Oracle R Enterprise Workflow"

"Getting Started with Oracle R Enterprise" describes the following operations:

Connecting to a database.
Creating Oracle R Enterprise proxy objects for database tables.
Moving data from a data.frame in your local R session to a database table, represented by an ore.frame proxy object, and the reverse.

"Preparing and Exploring Data in the Database" describes preparing data for analysis and exploring data. Preparing and exploring data may include operations such as the following:

Selecting data from a data set or table.
Cleaning the data by filtering out unneeded information.
Ordering the data.
Intermediate aggregations of data.
Time-series analysis.
Recoding or formatting of data.
Exploratory data analysis.

"Building Models in Oracle R Enterprise " describes building models, including Oracle Data Mining models, using functions in the OREmodels and OREdm packages.

" Predicting With R Models" describes using the ore.predict function on Oracle R Enterprise models.

"Using Oracle R Enterprise Embedded R Execution" describes how to create and execute R scripts in one or more R engines that run on the database server, and how to save those scripts in the Oracle R Enterprise script repository.