Predictive Analytics using Oracle Data Mining ( D91316)

Predictive Analytics using Oracle Data Mining ( D91316)

Overview

Duration: 2 Days 

This Predictive Analytics using Oracle Data Mining Ed 1 training will review the basic concepts of data mining. Expert Oracle University instructors will teach you how to leverage the predictive analytical power of Oracle Data Mining, a component of the Oracle Advanced Analytics option.

Learn To:

  • Explain basic data mining concepts and describe the benefits of predictive analysis.
  • Understand primary data mining tasks, and describe the key steps of a data mining process.
  • Use the Oracle Data Miner to build, evaluate, apply, and deploy multiple data mining models.
  • Use Oracle Data Mining’s predictions and insights to address many kinds of business problems.
  • Deploy data mining models for end-user access, in batch or real-time, and within applications.

Objectives

Upon completing this course, the learner will be able to meet these overall objectives:
  • Explain basic data mining concepts and describe the benefits of predictive analysis
  • Understand primary data mining tasks, and describe the key steps of a data mining process
  • Use the Oracle Data Miner to build, evaluate, apply, and deploy multiple data mining models
  • Use Oracle Data Mining’s predictions and insights to address many kinds of business problems
  • Deploy data mining models for batch or real-time access by end-users
Module 1: Introduction
Course Objectives
Suggested Course Prerequisites
Suggested Course Schedule
Class Sample Schemas
Practice and Solutions Structure
Review location of additional resources

Module 2: Predictive Analytics and Data Mining Concepts
What is the Predictive Analytics?
Introducting the Oracle Advanced Analytics (OAA) Option?
What is Data Mining?
Why use Data Mining?
Examples of Data Mining Applications
Supervised Versus Unsupervised Learning
Supported Data Mining Algorithms and Uses

Module 3: Understanding the Data Mining Process
Common Tasks in the Data Mining Process
Introducing the SQL Developer interface

Module 4: Introducing Oracle Data Miner 4.1
Data mining with Oracle Database
Setting up Oracle Data Miner
Accessing the Data Miner GUI
Identifying Data Miner interface components
Examining Data Miner Nodes
Previewing Data Miner Workflows

Module 5: Using Classification Models
Reviewing Classification Models
Adding a Data Source to the Workflow
Using the Data Source Wizard
Using Explore and Graph Nodes
Using the Column Filter Node
Creating Classification Models
Building the Models
Examining Class Build Tabs

Module 6: Using Regression Models
Reviewing Regression Models
Adding a Data Source to the Workflow
Using the Data Source Wizard
Performing Data Transformations
Creating Regression Models
Building the Models
Comparing the Models
Selecting a Model

Module 7: Using Clustering Models
Describing Algorithms used for Clustering Models
Adding Data Sources to the Workflow
Exploring Data for Patterns
Defining and Building Clustering Models
Comparing Model Results
Selecting and Applying a Model
Defining Output Format
Examining Cluster Results

Module 8: Performing Market Basket Analysis
What is Market Basket Analysis?
Reviewing Association Rules
Creating a New Workflow
Adding a Data Source to the Workflow
Creating an Association Rules Model
Defining Association Rules
Building the Model
Examining Test Results

Module 9: Performing Anomaly Detection
Reviewing the Model and Algorithm used for Anomaly Detection
Adding Data Sources to the Workflow
Creating the Model
Building the Model
Examining Test Results
Applying the Model
Evaluating Results

Module 10: Mining Structured and Unstructured Data
Dealing with Transactional Data
Handling Aggregated (Nested) Data
Joining and Filtering data
Enabling mining of Text
Examining Predictive Results

Module 11: Using Predictive Queries
What are Predictive Queries?
Creating Predictive Queries
Examining Predictive Results

Module 12: Deploying Predictive models
Requirements for deployment
Deployment Options
Examining Deployment Options
N/A
N/A
Course ID:
D91316


Show Schedule for: