Oracle Data Miner Extension for SQL Developer 4.0 Release Notes

Watch Demo on YouTube

December 2013

These release notes contain the following information about Oracle Data Miner 4.0:

  • Oracle Data Miner Functionality
  • New Features
  • Before You Start
  • Support
  • Getting Started
  • Migration
  • Learn How Use Data Miner
  • General Comments and Limitations

Oracle Data Miner Functionality

Oracle Data Mining, part of the Oracle Advanced Analytics option of Oracle Enterprise Edition, provides powerful data mining functionality to leverage data stored in an Oracle Database.

Oracle Data Miner is the graphical user interface (GUI) for Oracle Data Mining. Oracle Data Miner is an extension to Oracle SQL Developer.

Oracle Data Mining enables users to build descriptive and predictive models that

  • Predict customer behavior
  • Identify promising selling opportunities
  • Identify customer retention risks
  • Discover customer clusters, segments, and profiles
  • Detect anomalous behavior

For more information about Oracle Data Mining, see Oracle Data Mining on Oracle Technology Network.

New Features

The Oracle Data Miner extension to SQL Developer 4.0 includes these new features:

  • These features are supported for all database versions supported by Data Miner (Oracle Database 11.2.0.1 and above):
    • Workflow SQL Script Deployment
      • Generates SQL scripts to support full deployment of workflow contents
    • SQL Query Node
      • Integrate SQL queries to transform data or provide a new data source
      • Supports the running of R Language Scripts and viewing of R generated data and graphics
    • Graph Node
      • Generate Line, Scatter, Bar, Histogram and Box Plots
    • Workflow Performance Features
      • Workflow Parallel Query Setting: Specifies degree of parallel query processing desired per workflow node.
      • Table Compression: Table generation utilizes table compression feature.
    • Model Build Node Improvements
      • Node-level data usage specification applied to underlying models
      • Node-level text specifications to govern text transformations
      • Displays heuristic rules responsible for excluding predictor columns
      • Ability to control the amount of Classification and Regression test results generated
      • Model Tuning option, turn off/on generation of tuning results
    • View Data
      • Ability to drill in to view custom objects and nested tables
    • Model Details Node
      • Added Cluster Centroid Details
    • Explore and Transform Nodes
      • Improvements in NULL handling
    • Explore Node
      • Ability to select specific statistical outputs
    • Workflow Run and Validation Options
      • Ability to select multiple nodes when invoking Workflow Run options
      • Added Validation option that allows users to run the Workflow in validation mode
    • Workflow Import
      • Validate if the target database version supports the functionality contained in the imported workflow
    • Model Tuning
      • Added option to control generation of results used for post-model build tuning
    • Column Filter Node
      • Added System Determined option for Attribute Importance sampling technique
    • Model Test Performance
      • Specifying CASE ID improves performance of Classification and Regression testing
    • Viewers and Editors
      • Removed blocking dialogs triggered by long running processes and queries
    • Copy and Paste added functionality
      • Ability to copy charts to clipboard or save to file
      • Ability to copy data grids to clipboard
      • Ability to easily copy Cluster and Decision Tree Rules to clipboard or file
      • Ability to copy and paste workflows between different Data Miner repositories as long as the target repository is compatible with the source repository
    • Charts
      • Ability to view and copy data content of all charts
    • Demo Data
      • Added ODMR_CARS_DEMO table to the demo data scripts
    • Backup And Recovery
      • New scripts to provide workflow-level backup and recovery options
  • For Database 11.2.0.4 or higher, significant improvements in Data Miner Repository performance for workflow save, run, and load times
  • These features require connection to Oracle Database 12c Release 1 or above:
    • Predictive Query Nodes
      • Predictive results without the need to build models using Analytical Queries
      • Refined predictions based on data partitions
    • Clustering Node New Algorithm
      • Added Expectation Maximization algorithm
    • Feature Extraction Node New Algorithms
      • Added Singular Value Decomposition and Principal Component Analysis algorithms
    • Text Mining Enhancements
      • Text transformations integrated as part of Model's Automatic Data Preparation
      • Ability to import Build Text node specifications into a Model Build node
    • Prediction Result Explanations
      • Scoring details that explain predictive result
    • Generalized Linear Model New Algorithm Settings
      • New algorithm settings provide feature selection and generation
    • Extended Data Type Support
      • Support for VARCHAR2 size of 32767

Before You Start

To use Oracle Data Miner, you must connect to an Oracle Database that satisfies these requirements:

  • Oracle Data Mining is installed. Oracle Data Mining is installed automatically when you install Oracle Database Enterprise Edition.

    New features may require Oracle Database 12c Release 1.

  • Oracle Text is installed. Oracle Text is installed automatically when you install Oracle Database Enterprise Edition.

    If you plan to use Oracle Text to extract Themes, you must install the Knowledge Base by installing the Oracle Database Examples, as described in the Oracle Database Examples Installation Guide.

  • Oracle XML DB is installed. Oracle XML DB is installed automatically when you install Oracle Database Enterprise Edition.

  • Data used by the Oracle By Example tutorials requires the SH schema. If you install a starter database when you install Oracle Database Enterprise Edition, SH is automatically installed.

Data Miner has two components:

  • The Repository, which runs on an Oracle Database; one repository supports many connected clients; the connected clients, in turn, can either connect to their own database account or share a common database account.
  • The Client, which runs on any platform that SQL Developer supports (Windows, Mac, or Linux).

Support

For released products, you are supported by Oracle Support under your current Oracle Database Support license. Log Oracle Data Miner bugs and issues using My Oracle Support for the product.

You can post Data Miner questions or issues at Data Mining Forum and receive replies from other Data Miner users as well as from Oracle Data Mining Development team. You may find it useful to "follow" the Data Miner forum to keep up with useful postings.

Getting Started

Follow these steps to install the prerequisites for Data Miner and install the Data Miner Repository:

  • Step 1: Install Oracle 11 Release 2 or higher Database. To have access to all available data mining features install Oracle 12.1.

    • Download the software from Oracle Database Software Downloads.

    • To use Oracle Data Miner, you must connect to an Oracle Database that satisfies the requirements specified in Before You Start.
    • For Oracle Database 11g Release 2, the Oracle Data Miner Administrator's Guide describes how to install Oracle Database Enterprise Edition on Microsoft Windows. For instructions for other platforms, see Installing and Upgrading in the Oracle Database Documentation Library.

      For Oracle Database 12c Release 1, Oracle® Data Mining User's Guide describes Oracle Data Mining installation.

      Oracle Data Mining Documentation describes how to view Data Mining Documentation.

  • Step 2: Download SQL Developer 4.0 from SQL Developer. Install SQL Developer by unzipping the download to any directory on your system.

    Note that SQL Developer 4.0 requires Java version 1.7 and above.

  • Step 3: Install Data Miner Repository from the Data Miner GUI by following the Oracle By Example tutorial Setting Up Oracle Data Miner .

    Alternatively, you can install the Data Miner Repository using the Installation Scripts. The installation scripts are in SQLDevHome\sqldeveloper\dataminer\scripts, where SQLDevHome is the directory where you installed SQL Developer. Use of the scripts is optional. The scripts are described in SQLDevHome\sqldeveloper\dataminer\scripts/install_scripts_readme.html and in the online help for Data Miner.

    After you install SQL Developer 4.0, you can also view start up instructions for Data Miner as follows: Select the menu item Help>Table of Contents; in the Help Center, expand Data Miner Concepts and Usage and then expand Data Miner 4.0 and its subfolder Install Prerequisites and Oracle Data Miner Repository.

Oracle Data Mining Documentation

You can view or download Oracle documentation from Documentation. Go to Database to find the documentation library for your database. Oracle Data Mining is a component of the Oracle Advanced Analytics Option. Oracle Advanced Analytics is described on the Data Warehousing and Business Intelligence page.

Migration

When you initially open a connection from the Data Miner navigator to an existing Data Miner repository, you are prompted to update the repository. The repository update will be performed for you through the GUI-guided process.

If you want to perform migration by running scripts manually, the installation scripts are located in SQLDevHome\sqldeveloper\dataminer\scripts, where SQLDevHome is the directory where SQL Developer is installed. The scripts are described ininstall_scripts_readme.html in the scripts directory. and in the online help for Data Miner.

Learn How to Use Data Miner

Data Miner includes Oracle By Example (OBE) tutorials in the Oracle Learning Library at Oracle Data Mining 12c OBE Series. The OBEs describe how to set up and use Oracle Data Miner.

In-depth White Papers are available at Oracle Data Mining under the heading Technical Information for the following topics:

  • Generate a PL/SQL script for workflow deployment
  • Integrate Oracle R Enterprise Algorithms into workflow using the SQL Query node
  • Using Oracle Data Miner 11g Release 2 with Star Schema data - A Telco Churn Case Study

General Comments and Limitations

  • If a workflow appears to be running too long, you can use the Event Viewer to determine the status of the workflow. To open the Event Viewer, click the Event Viewer icon in the workflow tool bar. You can click on the Info icon in the toll bar of the Event Viewer to see the information event logs in addition to the Warnings and Errors.

    If the workflow is complete but the UI still shows that the workflow is running, simply close the workflow and reopen it.

  • When you upgrade to Oracle Database 11g Release 2 (11.2.0.4) or higher from 11.2.0.3 or lower, you must also upgrade the ODMRSYS repository. When you start SQL Developer 4.0 after the database upgrade, you are prompted to perform an upgrade for Data Miner. The upgrade process is fully automated in the Data Miner GUI.

  • Beginning with Oracle Database 12c, you can specify a maximum size of 32767 bytes for the VARCHAR2, NVARCHAR2, and RAW data types.

    You will have failures when you view data in an extended data type, that is, a VARCHAR2 column with a declared size of greater than 4000 bytes.

    In order to view extended data types, you must set the connection properties following these steps:

    1. In SQL Developer, go to Tools > Preferences > Database > Advanced.
    2. Click Use Oracle Client.
    3. Then click Configure.
    4. Set Client Type to Oracle Home and set Client Location to the value of Oracle Home for either a full Oracle 12c Client or for Oracle Database 12c installed on your local system. (Client Type equal to Instant Client does not work at the time of this release.)